Context exchange between devices in mobile environment

Context awareness is emerging on mobile devices. Context awareness can be used to improve usability of a mobile device. Context awareness is particularly important on mobile devices due the limitations they have. At first in this work, a literature review on context awareness and mobile environment is made. For aiding context awareness there exist an implementation of a Context Framework for Symbian S60 devices. It provides a possibility for exchanging the contexts inside the device between the client applications of the local Context Framework. The main contribution of this thesis is to design and implement an enhancement to the S60 Context Framework for providing possibility to exchange context over device boundaries. Using the implemented Context Exchange System, the context exchange is neither depending on the type of the context nor the type of the client. In addition, the clients and the contexts can reside on any interconnected device. The usage of the system is independent of the programming language since in addition to using only Symbian C++ function interfaces it can also be utilized using XML scripts. The Meeting Sniffer application, which uses the Context Exchange System, was also developed in this work. Using this application, it is possible to recognize a meeting situation and suggest device profile change to a user.

Design and Implementation of MUPE Server Context Tool for Eclipse IDE

The development of software tools begun as the first computers were built. The current generation of development environments offers a common interface to access multiple software tools and often also provide a possibility to build custom tools as extensions to the existing development environment. Eclipse is an open source development environment that offers good starting point for developing custom extensions. This thesis presents a software tool to aid the development of context-aware applications on Multi-User Publishing Environment (MUPE) platform. The tool is implemented as an Eclipse plug-in. The tool allows developer to include external server side contexts to their MUPE applications. The tool allows additional context sources to be added through the Eclipse's extension point mechanism. The thesis describes how the tool was designed and implemented. The implementation consists of tool core component part and an additional context source extension part. Tool core component is responsible for the actual context addition and also provides the needed user interface elements to the Eclipse workbench. Context source component provides the needed context source related information to the core component. As part of the work an update site feature was also implemented for distributing the tool through Eclipse update mechanism.

Usable Privacy Preservation in Mobile Electronic Personality

Personalised ubiquitous services have rapidly proliferated due technological advancements in sensing, ubiquitous and mobile computing. Evolving societal trends, business and the economic potential of Personal Information (PI) have overlapped the service niches. At the same time, the societal thirst for more personalised services has increased and are met by soliciting deeper and more privacy invasive PI from customers. Consequentially, reinforcing traditional privacy challenges and unearthed new risks that render classical safeguards ine ective. The absence of solutions to criticise personalised ubiquitous services from privacy perspectives, aggravates the situation. This thesis presents a solution permitting users' PI, stored in their mobile terminals to be disclosed to services in privacy preserving manner for personalisation needs. The approach termed, Mobile Electronic Personality Version 2 (ME2.0), is compared to alternative mechanisms. Within ME2.0, PI handling vulnerabilities of ubiquitous services are identi ed and sensitised on their practices and privacy implications. Vulnerability where PI may leak through covert solicits, excessive acquisitions and legitimate data re-purposing to erode users privacy are also considered. In this thesis, the design, components, internal structures, architectures, scenarios and evaluations of ME2.0 are detailed. The design addresses implications and challenges leveraged by mobile terminals. ME2.0 components and internal structures discusses the functions related to how PI pieces are stored and handled by terminals and services. The architecture focusses on di erent components and their exchanges with services. Scenarios where ME2.0 is used are presented from di erent environment views, before evaluating for performance, privacy and usability.

What are the opportunities and challenges of cloud computing technology in the healthcare information systems

This thesis discusses the opportunities and challenges of the cloud computing technology in healthcare information systems by reviewing the existing literature on cloud computing and healthcare information system and the impact of cloud computing technology to healthcare industry. The review shows that if problems related to security of data are solved then cloud computing will positively transform the healthcare institutions by giving advantage to the healthcare IT infrastructure as well as improving and giving benefit to healthcare services. Therefore, this thesis will explore the opportunities and challenges that are associated with cloud computing in the context of Finland in order to help the healthcare organizations and stakeholders to determine its direction when it decides to adopt cloud technology on their information systems.

Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.

The impact of a training program in phonological awareness on children's early writing

This study examined the effects that a training program in phonological awareness had on the early writing skills of children in a Grade One class in the Lincoln County Separate school system. The intent of the training program was to provide consistent and systematic practice in the manipulation of the phonological structure of language. The games and activities of the training program were related to a framework of developmental phonological skills and practised in a group setting during an unstructured period of the regular classroom schedule. The training program operated three days in a six-day cycle for approximately twenty minutes a day, from November until mid-March. All children were tested at the outset and conclusion of the study to determine level of functioning in letter identification, word recognition, verbal intelligence, phonological awareness and spelling. Results of the pre-tests and post-tests were compared to determine differences between the experimental and control groups over time. In addition, a systematic analysis of the children's writing looked at the development of the spelling of regular and irregular words. The results of this study provided strong support for the hypothesis that the treatment group would progress through the stages of early writing development more quickly than children without such training. On the basis of differences between the groups over time, it was evident that training in phonological awareness had a direct positive effect on the spelling of regular words for children during the early stages of writing. The training program did not have a significant effect on the spelling of irregular words. Test results evaluating phonological awareness indicated a significant difference within each group over time but no significance between the groups during the experimental period. It would appear that the results of these tests reflect maturational changes in the child rather than causal effects of the training program. Nor did the effects of the training program transfer significantly to other aspects of language. Although some of the hypotheses considered were not supported by the study, the results do indicate that children during the early stages of writing development can benefit from a training program in phonological awareness. The theoretical direction for effective programming as a result of this study is discussed. The educational implications of training phonological awareness concurrent to beginning efforts in writing are considered.

User Profile Management and Selection in Context-Aware Service Platforms for Networks Beyond 3G

In recent years, progress in the area of mobile telecommunications has changed our way of life, in the private as well as the business domain. Mobile and wireless networks have ever increasing bit rates, mobile network operators provide more and more services, and at the same time costs for the usage of mobile services and bit rates are decreasing. However, mobile services today still lack functions that seamlessly integrate into users’ everyday life. That is, service attributes such as context-awareness and personalisation are often either proprietary, limited or not available at all. In order to overcome this deficiency, telecommunications companies are heavily engaged in the research and development of service platforms for networks beyond 3G for the provisioning of innovative mobile services. These service platforms are to support such service attributes. Service platforms are to provide basic service-independent functions such as billing, identity management, context management, user profile management, etc. Instead of developing own solutions, developers of end-user services such as innovative messaging services or location-based services can utilise the platform-side functions for their own purposes. In doing so, the platform-side support for such functions takes away complexity, development time and development costs from service developers. Context-awareness and personalisation are two of the most important aspects of service platforms in telecommunications environments. The combination of context-awareness and personalisation features can also be described as situation-dependent personalisation of services. The support for this feature requires several processing steps. The focus of this doctoral thesis is on the processing step, in which the user’s current context is matched against situation-dependent user preferences to find the matching user preferences for the current user’s situation. However, to achieve this, a user profile management system and corresponding functionality is required. These parts are also covered by this thesis. Altogether, this thesis provides the following contributions: The first part of the contribution is mainly architecture-oriented. First and foremost, we provide a user profile management system that addresses the specific requirements of service platforms in telecommunications environments. In particular, the user profile management system has to deal with situation-specific user preferences and with user information for various services. In order to structure the user information, we also propose a user profile structure and the corresponding user profile ontology as part of an ontology infrastructure in a service platform. The second part of the contribution is the selection mechanism for finding matching situation-dependent user preferences for the personalisation of services. This functionality is provided as a sub-module of the user profile management system. Contrary to existing solutions, our selection mechanism is based on ontology reasoning. This mechanism is evaluated in terms of runtime performance and in terms of supported functionality compared to other approaches. The results of the evaluation show the benefits and the drawbacks of ontology modelling and ontology reasoning in practical applications.

Information Exchange and Fusion in Dynamic and Heterogeneous Distributed Environments

Context awareness, dynamic reconfiguration at runtime and heterogeneity are key characteristics of future distributed systems, particularly in ubiquitous and mobile computing scenarios. The main contributions of this dissertation are theoretical as well as architectural concepts facilitating information exchange and fusion in heterogeneous and dynamic distributed environments. Our main focus is on bridging the heterogeneity issues and, at the same time, considering uncertain, imprecise and unreliable sensor information in information fusion and reasoning approaches. A domain ontology is used to establish a common vocabulary for the exchanged information. We thereby explicitly support different representations for the same kind of information and provide Inter-Representation Operations that convert between them. Special account is taken of the conversion of associated meta-data that express uncertainty and impreciseness. The Unscented Transformation, for example, is applied to propagate Gaussian normal distributions across highly non-linear Inter-Representation Operations. Uncertain sensor information is fused using the Dempster-Shafer Theory of Evidence as it allows explicit modelling of partial and complete ignorance. We also show how to incorporate the Dempster-Shafer Theory of Evidence into probabilistic reasoning schemes such as Hidden Markov Models in order to be able to consider the uncertainty of sensor information when deriving high-level information from low-level data. For all these concepts we provide architectural support as a guideline for developers of innovative information exchange and fusion infrastructures that are particularly targeted at heterogeneous dynamic environments. Two case studies serve as proof of concept. The first case study focuses on heterogeneous autonomous robots that have to spontaneously form a cooperative team in order to achieve a common goal. The second case study is concerned with an approach for user activity recognition which serves as baseline for a context-aware adaptive application. Both case studies demonstrate the viability and strengths of the proposed solution and emphasize that the Dempster-Shafer Theory of Evidence should be preferred to pure probability theory in applications involving non-linear Inter-Representation Operations.

Security, trust and privacy supported by context-aware middleware

Driven by new network and middleware technologies such as mobile broadband, near-field communication, and context awareness the so-called ambient lifestyle will foster innovative use cases in building automation, healthcare and agriculture. In the EU project Hydra1 highlevel security, trust and privacy concerns such as loss of control, profiling and surveillance are considered at the outset. At the end of this project the Hydra middleware development platform will have been designed so as to enable developers to realise secure ambient scenarios especially in the user domains of building automation, healthcare, and agriculture. This paper gives a short introduction to the Hydra project, its user domains and its approach to ensure security by design. Based on the results of a focus group analysis of the building automation domain typical threats are evaluated and their risks are assessed. Then, specific security requirements with respect to security, privacy, and trust are derived in order to incorporate them into the Hydra Security Meta Model. How concepts such as context security, semantic security, and virtualisation support the overall Hydra approach will be introduced and illustrated on the basis of a technical building automation scenario.

Towards semantic resolution of security in ambient environments

Driven by new network and middleware technologies such as mobile broadband, near-field communication, and context awareness the so-called ambient lifestyle will foster innovative use cases in different domains. In the EU project Hydra high-level security, trust and privacy concerns such as loss of control, profiling and surveillance are considered at the outset. At the end of this project the. Hydra middleware development platform will have been designed so as to enable developers to realise secure ambient scenarios. This paper gives a short introduction to the Hydra project and its approach to ensure security by design. Based on the results of a focus group analysis of the user domain "building automation" typical threats are evaluated and their risks are assessed. Then, specific security requirements with respect to security, privacy, and trust are derived in order to incorporate them into the Hydra Security Meta-Model. How concepts such as context, semantic resolution of security, and virtualisation support the overall Hydra approach will be introduced and illustrated on the basis of it technical building automation scenario.

A new algorithm for tracking people in a pervasive mining environment

This paper analyze and study a pervasive computing system in a mining environment to track people based on RFID (radio frequency identification) technology. In first instance, we explain the RFID fundamentals and the LANDMARC (location identification based on dynamic active RFID calibration) algorithm, then we present the proposed algorithm combining LANDMARC and trilateration technique to collect the coordinates of the people inside the mine, next we generalize a pervasive computing system that can be implemented in mining, and finally we show the results and conclusions.

Prescription software for recovery and rehabilitation using Microsoft Kinect

Brain injuries, including stroke, can be debilitating incidents with potential for severe long term effects; many people stop making significant progress once leaving in-patient medical care and are unable to fully restore their quality of life when returning home. The aim of this collaborative project, between the Royal Berkshire NHS Foundation Trust and the University of Reading, is to provide a low cost portable system that supports a patient's condition and their recovery in hospital or at home. This is done by providing engaging applications with targeted gameplay that is individually tailored to the rehabilitation of the patient's symptoms. The applications are capable of real-time data capture and analysis in order to provide information to therapists on patient progress and to further improve the personalized care that an individual can receive.