WeLive project’s main objective is about transforming the current e-government approach by providing a new paradigm based on a new open model oriented towards the design, production and deployment of public services and mobile apps based on the collaboration of different stakeholders. These stakeholders form the quadruple helix, i.e., citizens, private companies, research institutes and public administrations. Through the application of open innovation, open data and open services paradigms, the framework developed within the WeLive project enables the co-creation of urban apps. In this paper, we extend the description of the WeLive platform presented at , plus the preliminary results of the first pilot phase. The two-phase evaluation methodology designed and the evaluation results of first pilot sub-phase are also presented.

In this work we performed a comparison between two different approaches to track a person in indoor environments using a locating system based on BLE technology with a smartphone and a smartwatch as monitoring devices. To do so, we provide the system architecture we designed and describe how the different elements of the proposed system interact with each other. Moreover, we have evaluated the system’s performance by computing the mean percentage error in the detection of the indoor position. Finally, we present a novel location prediction system based on neural embeddings, and a soft-attention mechanism, which is able to predict user’s next location with 67% accuracy.

Educational remote laboratories are a software and hardware tool that allows students to remotely access real equipment located in universities as if they were in a hands-on-lab session. Their integration in Content and Learning Management Systems (CMSs or LMSs) has been an active research topic for years, supporting mainly ad hoc solutions. A notable exception has been the use of federation protocols -commonly used for sharing laboratories from one university to other-, for actually sharing laboratories from a remote laboratory system to a C/LMS. This approach opened new doors in the simplification of the process, since it did not require the remote laboratories to make any type of change. The focus of this contribution is to provide a solution to decrease the number of functionalities required for creating an integration by providing a software component that reuses them. As shown in the contribution, this component has been implemented and two remote laboratory management systems (which provide access to multiple remote laboratories) are already supported, and a third one is under development. In the C/LMS side, all the LMSs supporting IMS LTI are supported, and HTTP APIs are provided for being supported by other systems. Indeed, the contribution describes its support in the Joomla CMS and in the Moodle 1.9 and dotLRN LMSs which do not support IMS LTI. The solution, called gateway4labs, is an open source initiative which targets to be used in production.

Behavior modeling has multiple applications in the intelligent environment domain. It has been used in different tasks, such as the stratification of different pathologies, prediction of the user actions and activities, or modeling the energy usage. Specifically, behavior prediction can be used to forecast the future evolution of the users and to identify those behaviors that deviate from the expected conduct. In this paper, we propose the use of embeddings to represent the user actions, and study and compare several behavior prediction approaches. We test multiple model (LSTM, CNNs, GCNs, and transformers) architectures to ascertain the best approach to using embeddings for behavior modeling and also evaluate multiple embedding retrofitting approaches. To do so, we use the Kasteren dataset for intelligent environments, which is one of the most widely used datasets in the areas of activity recognition and behavior modeling.

An educational remote laboratory is a software and hardware tool that allows students to remotely access real equipment located in the university as if they were in a hands-on-lab session. Federations of remote laboratories have existed for years: they are based on enabling two universities to exchange remote laboratories directly, without registering students of the latter on the former university. Integration of remote laboratories on Learning Management Systems (LMS) or Content Management Systems (CMS) have also been addressed in the past, enabling institutions to delegate the authentication or authorization of the experiments to the LMS/CMS. However, these integrations are usually achieved in an ad hoc way, integrating each particular laboratory to a LMS/CMS. This contribution studies the use of federation models to integrate remote laboratory management systems in LMS/CMSs, since both approaches (integrating a laboratory on an a external electronic learning tool, and integrating a laboratory on other laboratory) are essentially equivalent. The contribution defines two case studies to evaluate this approach, showing how this integration is achieved on a LMS (Moodle) and on a CMS (Joomla).