Miriam Gil

Personalization for unobtrusive service interaction

Increasingly, mobile devices play a key role in the communication between users and the services embedded in their environment. With ever greater number of services added to our surroundings, there is a need to personalize services according to the user needs and environmental context avoiding service behavior from becoming overwhelming. In order to prevent this information overload, we present a method for the development of mobile services that can be personalized in terms of obtrusiveness (the degree in which each service intrudes the user’s mind) according to the user needs and preferences. That is, services can be developed to provide their functionality at different obtrusiveness levels depending on the user by minimizing the duplication of efforts. On the one hand, we provide mechanisms for describing the obtrusiveness degree required for a service. On the other hand, we make use of Feature Modeling techniques in order to define the obtrusiveness level adaptation in a declarative manner. An experiment was conducted in order to put in practice the proposal and evaluate the user acceptance for the personalization capabilities provided by our approach.

Exploiting user feedback for adapting mobile interaction obtrusiveness

Ubiquitous computers, such as mobile devices, enable users to always be connected to the environment, making demands on one of the most precious resources of users: human attention. Thus, ubiquitous services should be designed in a considerate manner, demanding user attention only when it is actually required according to user needs. However, as user needs and preferences can change over time, we aim at improving the initial decisions by learning from users feedback through experience. We present a method for adapting interaction obtrusiveness automatically based on users reaction. Instead of asking the user to re-define his preferences about interaction obtrusiveness configurations, we learn them by means of the received feedback in a way that maximizes users satisfaction in a long-term use.

Designing for user attention: A method for supporting unobtrusive routine tasks

Abstract The automation of user routine tasks is one of the most important challenges in the development of Ambient Intelligence systems. However, this automation may be annoying since some tasks may grab users attention in inappropriate situations. Since user attention is a valuable resource, task automation must behave in a considerate manner demanding user attention only when it is required. To address this issue, this work presents a systematic method for supporting the design and automation of unobtrusive routine tasks that can adjust their obtrusiveness level at runtime according to the user attentional resources and context. This method proposes to design the routine tasks that the system must carry out and how they must interact with users in terms of obtrusiveness. The method also provides a software infrastructure that makes the execution of the tasks at the appropriate obtrusiveness degree a reality. Finally, the system has been validated by means of usefulness and performance tests and a practical case study that demonstrates the correctness and applicability of our approach without compromising system performance.

Adapting the Obtrusiveness of Service Interactions in Dynamically Discovered Environments

Due to the ubiquity of mobile devices, mobile service interactions (e.g., agenda notifications) may occur in any situation, leading to potential obtrusiveness (e.g., while in a meeting). In order to effectively adapt interaction obtrusiveness to suit the user’s situation, the user’s different situations should be defined in an unambiguous, generic and fine-grained way, while being valid across previously unknown, dynamically discovered environments. To realize this, we put the user in charge of defining his own situations, and exploit rich, descriptive environment information for defining and determining user situations. Our concrete approach aligns and extends two approaches, namely AdaptIO and SCOUT, to autonomously adapt mobile interactions in new, dynamically discovered environments. We supply a mobile user interface for defining situations, and validate it via an initial study with end-users.

Designing context-aware interactions for task-based applications

Since contextual information has potential to improve task-based applications, we provide an approach for integrating contextual information in task-based applications by considering simplicity as a major design goal. We present a context-aware application to support mobile workflows focusing our solutions in three important factors to organize and manage tasks: priority, location and time. Following the simplicity guidelines, we provide solutions based on these factors by means of visualizations that allow users to complete their tasks fluently on the go.

Designing the Human in the Loop of Self-Adaptive Systems

Self-adaptation is a key requirement in emerging software systems that must become capable of continuously adapting its behavior at run-time to their context (new environmental conditions, resource variability, unpredictable situations, changing user needs, etc.) without human intervention. However, experience in autonomous systems shows that people cannot be excluded entirely of the adaptation loop. For example, in the case of autonomous cars, they still need humans to drive in certain situations (e.g., complex driving situations, emergencies, etc.). This work defines the key factors to design the human participation in the control loops by introducing a framework to design human participations. Our framework considers human attention as a critical factor for user participation. Also, it pays attention to the dynamism between different types of human participation depending on the different system limitations (e.g., uncertainties in sensing, conflicts in goals, etc.) and the current user situation (e.g., user attention, environmental situation, etc.). We illustrate our approach by applying it to manage some actual autonomous cars situations that require human intervention.

Automating unobtrusive personalized services in ambient media environments

In the age of ambient media, people are surrounded by lots of physical objects (media objects) for rendering the digital world in the natural environment. These media objects should interact with users in a way that is not disturbing for them. To address this issue, this work presents a design and automation strategy for augmenting the world around us with personalized ambient media services that behave in a considerate manner. That is, ambient services are capable of adjusting its obtrusiveness level (i.e., the extent to which each service intrudes the user’s mind) by using the appropriate media objects for each user’s situation.

Self-adaptive unobtrusive interactions of mobile computing systems

This work has been developed with the support of MINECO under the project SMART-ADAPT TIN2013-42981-P, and co-financed by the Generalitat Valenciana under the postdoctoral fellowship APOSTD/2016/042.

Service obtrusiveness adaptation

Increasingly, mobile devices play a key role in the communication between users and the services embedded in their environment. All these services compete for the attentional resources of the user. Thus, it is essential to consider the degree in which each service intrudes the user mind (i.e., the obtrusiveness level) when services are designed. In this work we introduce a method for the development of mobile services that can be adapted in terms of obtrusiveness. That is, services can be developed to provide their functionality at different obtrusiveness levels by minimizing the duplication of efforts. In order to define the obtrusiveness level adaptation in a declarative manner we make use of Feature Modeling techniques. An experiment was conducted in order to put in practice the proposal and evaluate the user acceptance for the way in which services are presented.