Improving Mobile GIS applications through the identification of Geographic Context

Mobile devices are becoming increasingly popular. Their functionalities have become more than just making phone calls, due to regular improvements to these devices. Thus, with their notable increase in computational power, these devices have become able to support applications based on georeferenced data. By allowing the manipulation, visualisation and sharing of such data, these applications (supported by, for example, Google Maps or OpenStreetMap) have also shown an increasingly higher popularity. In this dissertation, we developed an adaptive Geographic Information System for Android devices, which displays relevant information to the user, based on the detected geographic context. The platform is supported by the concept of a context adaptation model, which enables the identification of particular situations in the context of the user, and the consequent adaptation of the application’s interface to the identified event. The context of the user is composed of the information collected by the sensors present in most mobile devices, which also enables the system to automatically adapt its content and thus become more relevant (according to the detected conditions), contributing for a better user experience. The relevant events to be listened to and the actions to be taken accordingly are managed in an administrator online tool, allowing for simplified software maintenance. By defining adaptation rules on aWeb platform, the administrators are able to configure the Android application’s behaviour without having to change the existing code. Finally, the developed platform was tested on a prototype of a Tourism application. The system was evaluated in two distinct parts - Web platform and Android application - by several participants, who agreed that the second is easy to use, while the first requires some previous learning.Os dispositivos móveis são cada vez mais populares. Devido a melhorias constantes destes dispositivos, as suas funcionalidades tornaram-se muito mais do que simplesmente efetuar chamadas. Assim, com a notável evolução do seu poder computacional, estes dispositivos passaram a ser capazes de suportar aplicações baseadas em dados georreferenciados. Ao possibilitar a manipulação, visualização e partilha de tais dados, estas aplicações (suportadas, por exemplo, por Google Maps ou OpenStreetMap) têm também apresentado um crescimento e popularidade cada vez maior. Nesta dissertação, foi desenvolvido um Sistema de Informação Geográfica adaptativo para dispositivos Android, que mostra informações relevantes ao utilizador, com base no contexto geográfico detetado. A plataforma é apoiada por um modelo de adaptação contextual, que permite a identificação de situações particulares no contexto do utilizador, e a consequente adaptação da interface da aplicação ao evento identificado. O contexto do utilizador é composto pelas informações recolhidas pelos sensores presentes na maioria dos dispositivos móveis, que também permite ao sistema adaptar automaticamente o seu conteúdo e, assim, tornar-se mais relevante (de acordo com as condições detectadas), contribuindo para uma melhor experiência de utilizador. Os eventos relevantes a serem tidos em conta e as ações a serem tomadas em conformidade são geridos através de uma ferramenta online de administrador, permitindo uma manutenção de software simples. Ao definir regras de adaptação numa plataforma Web, os administradores podem configurar o comportamento da aplicação Android sem precisar de alterar o código existente. Finalmente, a plataforma desenvolvida foi testada num protótipo de uma aplicação de Turismo. O sistema foi avaliado em duas partes - plataforma Web e aplicação Android - por vários participantes, que concordaram que a segunda é fácil de utilizar, enquanto a primeira requer alguma aprendizagem

CON-INFO: A Context-based Methodology for Designing and Assessing the Quality of Adaptable MUIs in Healthcare Applications

Mobile technology is an integral part of the modern healthcare environment. The mobile user interface (MUI) serves as the bridge between the application and healthcare professionals. It is important that the physician be able to easily express his needs on the MUI and correctly interpret the information displayed. However, there are many challenges that face the designer in designing and developing context-sensitive MUIs in this environment. The adaptability of the MUI is considered to be one of the most important issues to address. According to the World Health Organization (WHO), MUI adaptability is a major problem in the healthcare context. For the designer, the hope is that new technologies will be developed, such as mobile devices adaptable to different environments, to enable customization of the application to the user’s context. In this thesis, we propose a new methodology for designing a context-based adaptable MUI for healthcare applications. This methodology offers a new approach to automated MUI context adaptation, and provides a solution for both the provider (designer) of the healthcare application and the consumer (physician). New techniques for adapting MUIs offer new opportunities for the MUI designer to maximize the benefits of mobile health technology by providing the best possible way for healthcare professionals to perform their tasks efficiently and effectively. The proposed methodology is based on research contributions in four areas: (1) a new quality-in-use measurement model for validation purposes; (2) user stereotype modeling with a set of context descriptors, which formalize the domain expertise of the users; (3) context information modeling; and (4) use of the decision table technique to adapt the MUI features based on the context and the user stereotypes. The proposed quality-in-use model is inspired by the ISO/IEC 25010 and ISO/IEC 25022 international standards and adapted to healthcare applications. The first contribution is used in validating the quality-in-use of a software product developed according to the CON-INFO methodology, and the last three contributions are linked to form a methodology for development. The MUI features adapted to the needs of healthcare professionals have been implemented on the iPhone™ for validation purposes. An example of software for medical application is the Phoenix Health Information System (PHIS), which is in use at King Abdulaziz University Hospital (KAUH). PHIS2 is an updated desktop version developed based on Human-Computer Interaction (HCI) principles. A new mobile-based version of PHIS2 (PHIS2-M) has since been introduced, to make PHIS accessible from a mobile-based platform. The proposed context-based and rule-based approach for MUI feature adaptability resulted in a new version of PHIS2-M – PHIS2-MA (MA stands for mobile adaptation). This thesis validates the proposed methodology and clearly demonstrates its usefulness, providing details of the four empirical studies conducted with the end-users (physicians) in a real environment at the KAUH. The results of the formal studies reveal that our CON-INFO methodology for designing an adaptable MUI led to improvements to the current application and allowed researchers to test successive versions of the ‘final’ application