Eduardo Castillejo, PhD.

UCADAMI; User and Context-aware Dynamically Adaptable Mobile Interfaces

Tue, 31 Mar 2015 00:00:00 +0000

The aim of the UCADAMI project is to research in the creation of a technological framework that allows the dynamic adaptation of user interface based on the user and the context of use of interactive digital content consumed through mobile devices and its evaluation through data analysis and experimentation with users. This will require to: define user models that include their characteristics; create context recognition systems to automatically collect information as far as possible; define data models which retrieve the activity and the impact of the content in the user with the aim of achieving a better experience for all users through a universal, accessible and inclusive way for everybody.

SORELCOM; SOcial Routes Empowered by Linked COntents and context Mining

Tue, 31 Mar 2015 00:00:00 +0000

The main objective of SORELCOM is to provide a framework which will allow users to share and search cycle routes based on context data and impartial/unbiased information which will help to classify the current route. This classification will allow to find those routes which best fit the characteristics of the current user. SORELCOM will provide a website in which the user will be able to manage the produced data, and also a mobile application, through which the user will generate the corresponding information of the routes.

PIRAmIDE; Personalizable Interactions with Resources on AMI-Enabled Mobile Dynamic Environments

Tue, 31 Mar 2015 00:00:00 +0000

The PIRAmIDE project proposes to use user mobile device as a catalizer of the interaction of users with their environment, acting as a sixth sence which aids and assists us facilitating and improving our daily interactions with the objects that surround us in our workplace, home or public administrations.

MUGGES; Mobile User-Generated Geo Services

Tue, 31 Mar 2015 00:00:00 +0000

The MUGGES project focuses on services between mobile devices. It will develop basic components and market-ready mobile applications, in order to enable the provision, remote discovery and access of information from one mobile device directly (P2P) to another mobile device. The MUGGES project proposes the usage of GNSS Technology as the main driver of the mobile user-generated social-service paradigm, which represents a very clear current trend of business innovation.

DYNUI; Capability and Context-aware Dynamic Adaptation of User Interfaces for Ambient Assisted Living

Tue, 31 Mar 2015 00:00:00 +0000

The aim of DYNUI is to define an intelligent platform that facilitates the development and deployment of user-environment interfaces adaptable to the users, their interaction devices and their context. These interfaces have to be adapted both at the beginning and during the execution of services taking into account the users' capacities, their interaction devices and the users' and their environment's current context.

Dynamic User Interface Adaptation Engine Through Semantic Reasoning And Modelling in Mobile Devices

Mon, 09 Mar 2015 00:00:00 +0000

Official announcement in MORElab's website here.

Supervisors:

The VIVA panel was formed by:

José Bravo (President, from Universidad de Castilla la Mancha).
Vicente Pelechano from Universidad Politécnica de Valencia.
Pablo Orduña, from Universidad de Deusto.

Since the birth of the first GUI, adaptive user interfaces have been used to cover a wider range of possibilities seeking alternatives for the presentation of the information. Starting with small personalization features, more related to practical interaction, first customizable menus and graphical elements arose. Subsequently, the possibility of breaking down the interaction barriers has grown. From the user perspective, these limitations are usually caused by physiological disabilities, which imped users to properly interact with or consume information.

With the arrival of mobile telephony and portable devices, a wider range of possibilities regarding adaptive user interfaces have emerged. This market evolves continuously,bringing smaller, more powerful and wearable devices. This trend has strengthened the adaptive user interfaces within this market. Nevertheless, the user interface adaptation for these devices is far from the advances in static devices, which are able to perform complexer computations. Besides, more problems are added to the equation if the context is considered. The context situation, characterized by the set of singular features which define it and their quality might make the context dynamic. Thus, in each case, different adaptations or configurations might be needed. In fact, users may suffer from specific and/or temporary disabilities due to the context situation. This issue brings new challenges to adaptive user interfaces systems. Hence, from these challenges new adaptive tools started to be included and integrated with the purpose of minimising the identified interaction barriers. This also aimed to allow users to feature a sufficient interaction experience.

In this dissertation these problems are faced, aiming to reduce the boundaries between the user and the device in several limiting situations. To solve them, a dynamic and mobile user adaptation system is presented, principally supported by a semantic model which includes a conceptualization of the user, the current context and the device. Its design allows increasing the expressiveness of the user interaction contextual and interaction needs, also taking into account the features provided by the user's device.

Ontology Based Model for Supporting Dynamic and Adaptive User Interfaces

Mon, 31 Mar 2014 00:00:00 +0000

Adaptive user interfaces involves the design of dynamic interfaces whose main purpose is to present an adapted alternative to the user to ease the interaction. User’s preferences, context situation and device’s capabilities help these systems to adapt the interface to make the interaction more adequate to the current situation. Being aware of different characteristics of these entities is vital for reaching the main goals of these systems efficiently. To collect knowledge from these entities, it is necessary to design several formal models to help to organize and give meaning to the gathered data. In this paper, we analyse several literature solutions for modelling users, context and devices considering different approaches. We identify their advantages and drawbacks to finally propose a new ontology model which addresses the identified limitations.

Modelling users, context and devices for adaptive user interface systems

Mon, 31 Mar 2014 00:00:00 +0000

Purpose – The purpose of this paper is to review the state-of-the-art in adaptive user interface systems by studying their historical development over the past 20 years. Moreover, this paper contributes with a specific model combining three main entities (users, context and devices) that have been demonstrated to be always represented in these environments. Novel concepts that should be taken into account in these systems are also presented. Design/methodology/approach – The authors first provide a review and a comparison of current user interface adaptive systems. Next, the authors detail the most significant models and the set of techniques used to, finally, propose a novel model based on the studied literature. Findings – Literature solutions for adaptive user interface systems tend to be very domain dependant. This situation restricts the possibility of sharing and exporting the information between such systems. Furthermore, the studied approaches barely highlight the dynamism of these models. Originality/value – The paper is a review of adaptive user interface systems and models. Although there are several reviews in this area, there is a lack of research for modelling users, context and devices simultaneously in this domain. The paper also presents several significant concepts that should be taken into account to bring an adaptive and dynamic perspective to the studied models.

Modeling Users, Context and Devices for Ambient Assisted Living Environments

Mon, 31 Mar 2014 00:00:00 +0000

The participation of users within AAL environments is increasing thanks to the capabilities of the current wearable devices. Furthermore, the significance of considering user’s preferences, context conditions and device’s capabilities help smart environments to personalize services and resources for them. Being aware of different characteristics of the entities participating in these situations is vital for reaching the main goals of the corresponding systems efficiently. To collect different information from these entities, it is necessary to design several formal models which help designers to organize and give some meaning to the gathered data. In this paper, we analyze several literature solutions for modeling users, context and devices considering different approaches in the Ambient Assisted Living domain. Besides, we remark different ongoing standardization works in this area. We also discuss the used techniques, modeled characteristics and the advantages and drawbacks of each approach to finally draw several conclusions about the reviewed works.

Adapting user interfaces based on user preferences and habits

Mon, 31 Mar 2014 00:00:00 +0000

In the last few years, an ecosystem of devices and heterogeneous services has emerged with a huge variety of capacities and characteristics. These new devices, along with applications and services, must be used to enhance the quality of life, making the users daily activities easier, as well as increasing their personal autonomy. In this sense, there is a clear need for creating interfaces that adapt themselves taking into account characteristics of the user, context, application and device. One of the aspects to consider when adapting interfaces is the set of preferences of the user. When using different applications or devices, each user has different preferences, mainly related to their limitations. For that, we have developed a system that discovers users preferences related to different devices and applications. The system discovers set-up parameters, as well as normal performance parameters.