Advanced HCI and 3D Web over Low performance Devices

This position paper presents the authors’ goals on advanced human computer interaction and 3D Web -- Previous work on speech, natural language processing and visual technologies has achieved the development of the BerbaTek language learning demonstrator, a 3D virtual tutor that supports Basque language students through spoken interaction -- Next steps consist on migrating all the system to multidevice web technologies -- This paper shows the architecture defined and the steps to be performed in the next month

MHP Oriented Interactive Augmented Reality System for Sports Broadcasting Environments

Television and movie images have been altered ever since it was technically possible. Nowadays embedding advertisements, or incorporating text and graphics in TV scenes, are common practice, but they can not be considered as integrated part of the scene. The introduction of new services for interactive augmented television is discussed in this paper. We analyse the main aspects related with the whole chain of augmented reality production. Interactivity is one of the most important added values of the digital television: This paper aims to break the model where all TV viewers receive the same final image. Thus, we introduce and discuss the new concept of interactive augmented television, i. e. real time composition of video and computer graphics - e.g. a real scene and freely selectable images or spatial rendered objects - edited and customized by the end user within the context of the user's set top box and TV receiver

Refinery 4.0, a Review of the Main Challenges of the Industry 4.0 Paradigm in Oil & Gas Downstream

Industry 4.0 concept has become a worldwide revolution that has been mainly led by the manufacturing sector. Continuous Process Industry is part of this global trend where there are aspects of the “fourth industrial revolution” that must be adapted to the particular context and needs of big continuous processes such as oil refineries that have evolved to control paradigms supported by sector-specific technologies where big volumes of operation-driven data are continuously captured from a plethora of sensors. The introduction of Artificial Intelligence techniques can overcome the current limitations of Advanced Control Systems (mainly MPCs) by providing better performance on highly non-linear and complex systems and by operating with a broader scope in terms of signals/data and sub-systems. Moreover, the state of the art of traditional PID/MPC based solutions is showing an asymptotic improvement that requires a disruptive approach in order to reach relevant improvements in terms of efficiency, optimization, maintenance, etc. This paper shows the key aspects in oil refineries to successfully adopt Big Data and Machine Learning solutions that can significantly improve the efficiency and competitiveness of continuous processes