Smart-RBAC

Generally, smart campus applications do not consider the role of the user with his/her position in a university environment, consequently irrelevant information is delivered to the users. This dissertation proposes a location-based access control model, named Smart-RBAC, extending the functionality of Role-based Access Control Model (RBAC) by including user’s location as the contextual attribute, to solve the aforementioned problem. Smart-RBAC model is designed with a focus on content delivery to the user in order to offer a feasible level of flexibility, which was missing in the existing location-based access control models. An instance of the model, derived from Liferay’s RBAC, is implemented by creating a portal application to test and validate the Smart-RBAC model. Additionally, portlet-based applications are developed to assess the suitability of the model in a smart campus environment. The evaluation of the model, based on a popular theoretical framework, demonstrates the model’s capability to achieve some security goals like “Dynamic Separation of Duty” and “Accountability”. We believe that the Smart-RBAC model will improve the existing smart campus applications since it utilizes both, role and location of the user, to deliver content.

Contributions towards smart cities : exploring block level census data for the characterization of change in Lisbon

The interest in using information to improve the quality of living in large urban areas and its governance efficiency has been around for decades. Nevertheless, the improvements in Information and Communications Technology has sparked a new dynamic in academic research, usually under the umbrella term of Smart Cities. This concept of Smart City can probably be translated, in a simplified version, into cities that are lived, managed and developed in an information-saturated environment. While it makes perfect sense and we can easily foresee the benefits of such a concept, presently there are still several significant challenges that need to be tackled before we can materialize this vision. In this work we aim at providing a small contribution in this direction, which maximizes the relevancy of the available information resources. One of the most detailed and geographically relevant information resource available, for the study of cities, is the census, more specifically the data available at block level (Subsecção Estatística). In this work, we use Self-Organizing Maps (SOM) and the variant Geo-SOM to explore the block level data from the Portuguese census of Lisbon city, for the years of 2001 and 2011. We focus on gauging change, proposing ways that allow the comparison of the two time periods, which have two different underlying geographical bases. We proceed with the analysis of the data using different SOM variants, aiming at producing a two-fold portrait: one, of the evolution of Lisbon during the first decade of the XXI century, another, of how the census dataset and SOM’s can be used to produce an informational framework for the study of cities.