Resumen de Automating routine tasks in smart environments. A context-aware model-driven approach

Estefanía Serral Asensio

• Ubiquitous and Pervasive computing put forth a vision where environments are enriched with devices that provide users with services to serve them in their everyday lives. The building of such environments has the final objective of automating tedious routine tasks that users must perform every day.

  This automation is a very desirable challenge because it can considerably reduce natural resource consumption and improve users' quality of life by 1) making users' lives more comfortable, eficient, and productive, and 2) helping them to stop worrying and wasting time in performing tasks that need to be done and that they do not enjoy. However, the automation of user tasks is a complicated and delicate matter because it may bother users, interfere in their goals, or even be dangerous. To avoid this, tasks must be automated in a non-intrusive way by attending to users' desires and demands.

  This is the main goal of this thesis, that is, to automate the routine tasks that users want the way they want them. To achieve this, we propose two models of a high level of abstraction to specify the routines to be automated. These models provide abstract concepts that facilitate the participation of end-users in the model specification. In addition, these models are designed to be machine-processable and precise-enough to be executable models.

  Thus, we provide a software infrastructure that is capable of automating the specified routines by directly interpreting the models at runtime. Therefore, the routines to be automated are only represented in the models. This makes the models the primary means to understand, interact with, and modify the automated routines. This considerably facilitates the evolution of the routines over time to adapt them to changes in user behaviour. Without this adaptation, the automation of the routines may not only become useless for end-users but may also become a burden on them instead of being a help in their daily life. In our approach, the evolution of the automated routines is achieved by simply updating the models. As soon as the models are changed, the changes are also taken into account by the software infrastructure that interprets them to execute the routines. To support this evolution, our approach provides high-level mechanisms as well as a graphical tool that allow the routines to be evolved at runtime by updating the models.

  The proposal has been validated by following a case study based evaluaction in which end-users have participated. This validation has proven that our approach is capable of automating the routine tasks that users want to be automated the way they want them to be.