The success of smart mobile platforms and modern wearable computers, has boosted the evolution of Internet of Things (IoT) from a far-fetched futuristic vision to a reachable reality. These devices provide valuable data coming from human beings, ambient or IoT infrastructure, enabling a new world of context aware service and applications.
However, despite the IoT emanation, and although much research has been carried out on the impact that emotions have on several domains (such as health, social relationships, working life or emergencies), there is still a lack of pervasive environments that take into account emotional behaviour. This master thesis aims to bridge this gap, and proposes the development of an IoT platform that recognises emotions, merges data and user context, and personalises the user environment according to their context.
The development of this platform is the main goal of this master thesis. The intelligent system developed must be able to capture emotions by mean of analysing data that comes from cameras and several sensors (e.g. biometric or ambient), and to automatically adapt the environment to these emotions. In order to facilitate the automation process in the intelligent environment, the platform will be based on ECA (Event-Condition-Action) rules, allowing the user to automate tasks in an easy way.
While the system will be designed with the purpose of making straightforward its integration and configuration in any place, this project focuses on its implementation in a smart office scenario. For this purpose, the system will be deployed into a living lab, where all components and features will be tested by real users in a real scenario. In addition, with the purpose of enabling the realization of large-scale experiments at negligible cost, the system will also be deployed into a social simulated scenario. This scenario will consist of a simulation of a smart office, where sensor networks and users' emotions will be simulated with realistic environment models.
This master thesis will start with an exhaustive study of the state of art, where the current technologies involved in emotion analysis, social simulation and IoT will be analysed. Then, the requirements analysis will be done, in order to define all the objectives that the system architecture must achieve. The architecture design will be the next step. Finally, once the architecture has been designed, the system will be implemented and evaluated in a living lab and in a social simulated scenario.