Manuel García-Herranz

A Mechanism for Solving Conflicts in Ambient Intelligent Environments

Ambient Intelligence scenarios describe situations in which multitude of devices and agents live together. In this kind of scenarios is frequent to see the appearance of conflicts when modifying the state of a device as for example a lamp. Those problems are not as much of sharing of resources as of conflict of orders coming from different agents. This coexistence must deal also with the desire of privacy of the different users over their personal information such as where they are, what their preferences are or to whom this information should be available. When facing incompatible orders over the state of a device it turns necessary to make a decision. In this paper we propose a centralised mechanism based on prioritized FIFO queues to decide the order in which the control of a device is granted. The priority of the commands is calculated following a policy that considers issues such as the commanders role, commands type, contexts state and commander-context and commander-resource relations. Finally we propose a set of particular policies for those resources that do not adjust to the general policy. In addition we present a model pretending to integrate privacy through limiting and protecting contextual information.

Do not disturb: physical interfaces for parallel peripheral interactions

Interaction is, intrinsically, a multi-thread process. Supported by our various senses, our ability to speak, and the structure of our body and mind we can get simultaneously involved in multiple interactions, using different resources for each of them. This paper analyses natural interactions and the impact of using parallel channels in peripheral interactions. Applying a similar approach to human-computer interaction, we present a Tangible User Interface proof of concept to analyze the advantages and weakness of parallel interaction in computer-based systems. To this end, two tangible applications -to control the profile status in social networks and to control an Intelligent Room- are compared to their usual graphical counterparts, presenting the results of a user study and analyzing the implications of its results.

Easing the Smart Home: A rule-based language and multi-agent structure for end user development in Intelligent Environments

The present paper summarizes the Phd Dissertation of Manuel Garcia-Herranz [1] including the oral defenses.

Harnessing the Interaction Continuum for Subtle Assisted Living

People interact with each other in many levels of attention, intention and meaning. This Interaction Continuum is used daily to deal with different contexts, adapting the interaction to communication needs and available resources. Nevertheless, computer-supported interaction has mainly focused on the most direct, explicit and intrusive types of human to human Interaction such as phone calls, emails, or video conferences. This paper presents the results of exploring and exploiting the potentials of undemanding interaction mechanisms, paying special attention to subtle communication and background interaction. As we argue the benefits of this type of interaction for people with special needs, we present a theoretical framework to define it and propose a proof of concept based on Augmented Objects and a color codification mechanism. Finally, we evaluate and analyze the strengths and limitations of such approach with people with cognitive disabilities.

Adaptive Interfaces for People with Special Needs

This paper covers those aspects of modern interfaces which expand and enhance the way in which people interact with computers, like multi-touch table systems, presence-detection led displays and interactive virtualized real-life environments. It elaborates on how disabled or conditioned people take great advantage of natural interaction as interfaces adapt to their needs; interfaces which can be focused towards memory, cognitive or physical deficiencies. Applications size-up to serve specific users with customized tools and options, and are aware while taking into account the state and situation of the individual.

Easing the Smart Home: Translating Human Hierarchies to Intelligent Environments

Ubiquitous computing research have extended traditional environments in the so---called Intelligent Environments. All of them use their capabilities for pursuing their inhabitantss satisfaction, but the ways of getting it are most of the times unclear and frequently unshared among different users. This last problem becomes patent in shared environments in which users with different preferences live together. This article presents a solution translating human hierarchies to the Ubicomp domain, in a continuing effort for leveraging the control capabilities of the inhabitants in their on---growing capable environments. This mechanism, as a natural ubicomp extension of the coordination mechanism used daily by humans, has been implemented over a real environment: a living room equipped with ambient intelligence capabilities, and installed in two more: an intelligent classroom and an intelligent secure room.

Mind the gap: Impact on learnability of user interface design of authoring tools for teachers

Abstract Few teachers include information and communication technology in the classroom, despite their potential for increasing attention and motivation for students. Educational authoring tools are intended to turn teachers into designers and deliverers of technology-enhanced educational content, and increasing the adoption of these tools is a key element for speeding up this transformation. This paper emphasizes the importance of learnability for preventing rejection or abandonment by of such an authoring tool, and how acceptance is deeply affected by the interaction paradigm and the creation metaphor used in the tool. We present an analysis comparing two design paradigms: the widespread menu-based and choice-guided interaction paradigm versus a consistent metaphor with direct manipulation. The latter was implemented in DEDOS-Editor, a novel authoring tool that allows the creation of diverse educational activities that can be performed on different devices, such as PCs, digital blackboards, tablets, and multitouch surfaces. An experimental study shows the tremendous impact that interface choices have on the tools learning curve. The results provide the first mapping of the choice of a direct-manipulation interface and its effect on the learning curves entry point, as well as a consistent interaction metaphor with smoother and fast-growing learning curves. This allows users to complete more tasks and gain more knowledge through experience, in contrast to menu-based interfaces. The initial use of the tool is thus made easier for users with no experience or information about the tool, and the advantages of experience and expertize in facing new challenges are facilitating. This work also highlights the appropriateness of learning curves as a tool for measuring learnability.

DEDOS: An authoring toolkit to create educational multimedia activities for multiple devices

Information and Communication Technologies offer new possibilities for teachers to enhance their teaching methods. The increasing use of personal computers, tablets, interactive whiteboards, or even multitouch tabletops in the classrooms seems to attract the interest of the students. However, there are not many tools that allow teachers to create multimedia activities for all these technologies in an effortless way. Most of current authoring tools either focus on creating content for only one device or they do not fully exploit the benefits of rich content for designing engaging educational activities. In this paper, we present an authoring toolkit composed by two applications: DEDOS-Editor, which allow teachers to design their own learning activities, and DEDOS-Web, which allows the students to perform those activities adapting them to multiple devices. To test both tools, we have performed two evaluations. One with teachers to test the authoring tools and a second one with primary school students to test if the activities designed with this tool enhance their learning process. Results show that DEDOS-Editor is an easy to learn authoring tool which helps teachers to complement their learning methods while DEDOS-Web is flexible enough to create several learning scenarios from just one set of activities, factors which lead to achieving positive learning outcomes.

Personal ambient intelligent reminder for people with cognitive disabilities

The high number of people with Cognitive Disabilities (CD) is a serious social issue. A significant number of workers in the society provide care to family members with CD. The working caregivers either need to reschedule their working hours or spend less time with their elders. This article proposes PAIR, a Personal Ambient Intelligent Reminder that is designed to assist subjects with CD, their caregivers and the health professionals in an intelligent environment. Its goal is twofold: i) to create schedules that support complex temporal relationships between activities; ii) to generate a set of rules as a reminder agent to be included in an ambient intelligent environment in order to remind the patients and caregivers about the daily activities of the patient.

Evolutionary Feature Extraction to Infer Behavioral Patterns in Ambient Intelligence

Machine learning methods have been applied to infer activities of users. However, the small number of training samples and their primitive representation often complicates the learning task. In order to correctly infer inhabitant’s behavior a long time of observation and data collection is needed. This article suggests the use of MFE3/GA\(^{D\!R}\), an evolutionary constructive induction method. Constructive induction has been used to improve learning accuracy through transforming the primitive representation of data into a new one where regularities are more apparent. The use of MFE3/GA\(^{D\!R}\) is expected to improve the representation of data and behavior learning process in an intelligent environment. The results of the research show that by applying MFE3/GA\(^{D\!R}\) a standard learner needs considerably less data to correctly infer user’s behavior.