ABSTRACT
Ubiquitous environments are not fixed in time. Entities are constantly evolving;they are dynamic. Ubiquitous applications therefore have a strong need to adapt during their execution and react to the context changes, and developing ubiquitous applications is still complex. The use of the separation of needs and model-driven engineering present the promising solutions adopted in this approach to resolve this complexity. The authors thought that the best way to improve efficiency was to make these models intelligent. That's why they decided to propose an architecture combining machine learning with the domain of modeling. In this article, a novel tool is proposed for the design of ubiquitous applications, associated with a graphical modeling editor with a drag-drop palette, which will allow to instantiate in a graphical way in order to obtain platform independent model, which will be transformed into platform specific model using Acceleo language. The validity of the proposed framework has been demonstrated via a case study of COVID-19. © 2023 IGI Global. All rights reserved.
ABSTRACT
The present study propose a smart tooled process based on an MDA approach for the design of ubiquitous applications taking into account context information in order to deliver high-added value services. We will present our platform-independent model (PIM) associated with a graphical modeling workshop (editor) which will allow us to instantiate in a graphical way in order to obtain PIM models, which will be transformed into PSM. We illustrate its implementation on a prototype application in a pervasive environment that tracks the movements of persons who have tested positive to anticipate COVID-19 contaminations. © 2021 IEEE.