Êxodo Framework: uma solução para modelagem do comportamento de ambientes para Internet das Coisas

Abstract

The Internet of Things or IoT is a paradigm of computing in which devices and objects of the physical world (e.g. televisions, refrigerators and conditioners air) are connected through the Internet, providing services and exchanging information between in a global scale. This new paradigm has led the market to present solutions that increasingly bring IoT closer to everyday life. Manufacturers such as Samsung, Philips, GE and Belkin already have hardware solutions (e.g. smartphones, smart TV, smart plugs and sensors) that allow users to interact with the environment, and can turn on, off and even view statistical data on power consumption these devices. However, the main platforms that allow IoT to be enabled are still little used due to their complexity, being restricted only to expert users, that is, users who have technical knowledge in IoT, not allowing non- expert users to adapt these solutions and create environments for IoT according to your needs. In this context, this work presents the Exodus framework, a new approach to IoT with a focus on expert user and non-expert user. Exodus is a solution for IoT that can be extended and adapted to meet the different needs of the environment such as the inclusion of new devices and services and / or the definition of new behaviors to the environment. In order to define the different behavior that the environment can take, the Exodus has a graphical solution that makes use of a conceptual model called BDM4IoT (Behavior Definition Model for Internet of Things Ecosystems) that together allow the users to model the behavior of the environment according to With their needs, allowing them to create from simple models such as a home lighting scheme to more complex models such as the behavior of a production line in an industrial environment. The results obtained with experiments carried out with the BDM4IoT model and with the graphical tool, demonstrate the efficiency of this approach, allowing the inclusion of non-expert users in processes previously performed only by IoT specialists.