Ενδεικτικά αποτελέσματα

User Experience Evaluation Framework for Intelligent Environments (2017): A conceptual and methodological framework, describing attributes that should be evaluated for Ambient Intelligence environments, as well as for systems and applications in AmI environments. The framework provides concrete metrics, and specifies the methods that should be employed for their evaluation.
https://doi.org/10.3390/technologies9020041

UXAmI Observer (2017): UXAmI Observer is a tool that facilitates the process of reviewing and analyzing data from user-based experiments in intelligent environments and simulation spaces. The tool provides automated measurements of users’ interactive behavior, eliminating the need for extensive recording and notetaking from the evaluation observers. Furthermore, it provides insights and statistics of the overall user experience, while it supports various user-based experiment types, from task-based to in-situ, and long-term real usage.
https://doi.org/10.1007/978-3-030-01054-6_94

UXAmI Inspector (2017): UXAmI Inspector aims to facilitate evaluators in carrying out expert-based reviews for systems and applications in intelligent environments. Based on crowdsourcing, the tool retrieves guidelines relevant for a specific system or application that will be evaluated. The knowledge acquired through crowdsourcing is an effective approach towards addressing the inherent complexity of guidelines-based evaluation of AmI environments. Furthermore, the tool provides assistive facilities to evaluators for identifying their evaluation target(s) within an AmI environment, and actually carrying out the review process, involving multiple experts.

MockArt (2017): A management system for the creation of interactive UI prototypes and their use in user-based evaluation experiments (e.g. scenarios, AB testing). It constitutes a web-based platform that: (i) simplifies management of UI designs (e.g. correlations of screens and system requirements, version control), (ii) enables the creation of interactive online prototypes and (iii) supports the entire workflow of expert-based evaluation experiments: preparation, execution, consolidation of comments from individual reviewers, analysis of results and dissemination of findings.

Mockups Commenter (2017): A web application for collecting feedback from users on interactive prototypes.

Rewarding schemes for User-Generated Video Online Communities (2017): A gamification rewarding mechanism in order to motivate users towards knowledge sharing, encourage active engagement, and foster high quality contributions.
https://doi.org/10.5281/zenodo.834200

Multimodal Interaction In the Intelligent Living Room (2017): A suite of input/output channels that enable interaction even when a user’s primary channel is occupied, unavailable or non-existent, including:

• Virtual pointer. Users can control the TV interface by hovering their hand over the Leap Motion sensors which are embedded in the the side arms of a smart sofa. A virtual cursor that follows the movements of their hands, enables them to focus on and select areas of interest
• Mid-air gestures. Appropriate mid-air gestures, such as palm tilt, finger pinch, and hand swipe, are also available in order to permit users to complete specific actions (e.g. volume up/down, next/previous item in a list, zoom in/out etc.) quickly and in a natural manner.
• Touch. Through a Kinect sensor installed on top of the TV facing directly at the coffee table’s surface, the coffee table becomes a touch-enabled surface. Depending on the context of use, the table is able to display various interactive touch-enabled controls (e.g. play or pause a movie, move to next or previous item on a list).
• User posture. The force-sensitive resistors and load sensors which are installed in the smart sofa’s back and under its bottom pillows provide information regarding the user’s posture while seated (i.e. user leans back or forward). That way, when interactive controls appear on the augmented table, they are displayed within the user’s reach area.
• User presence. The force-sensitive resistors and load sensors of the smart sofa, along with the motion sensor -mounted on the ceiling, permit the detection of user presence inside the room. Knowing when one or more users are inside or leaving the room is quite important for deciding when to start or pause specific applications (e.g. turn on the TV when someone is in the living room, pause the movie when a user leaves the living room, etc.)
• Object Detection. When a physical object is placed on top of the augmented table, its presence can be identified via sophisticated software. This software cannot identify the type of the object, but it can estimate the space it occupies. That way, the interfaces projected on the coffee-table get rearranged in order to display the available information in areas that do not get hidden by the identified object(s).
• Remote Control. A three-dimensional gyroscopic remote control can be used as a mouse or keyboard. In its front side, it includes on/off buttons, navigation arrows and arithmetic controls. Its back side includes a keyboard that enables text input.
• the users can also record short phrases as vocal messages.

https://doi.org/10.3390/s19225011
https://doi.org/10.1145/3197768.3201548

InPrinted Framework (2017): InPrinted constitutes a framework supporting printed matter augmentation and user interaction with Ambient Intelligence (AmI) technologies in Smart Environments. The framework provides: (a) an open architecture enabling integration of new types of technologies for information acquisition and provision (b) independency of the development technologies for the applications (c) an extensible ontology based reference model for printed matter, as well as context-awareness mechanisms (d) implementation of printed matter augmentation mechanisms in the environment (e) support for multimodal natural interaction with printed matter in smart environments.
https://doi.org/10.1007/s11042-018-7088-9

PaaSage (2014): Design of a novel social networking platform for professionals targeting the community of DevOps engineers. The network combines community knowledge with information from two repositories, Chef Supermarket and the CAMEL repository of application models and executions, to improve the configuration, deployment, and optimization of distributed multi-cloud applications, tasks of major interest to cloud deployment specialists. The design of the professional network applied best practices aiming to support the creation of a vigorous community, to allow users to retrieve timely and appropriate information and to carry out actions in a small number of steps.
https://doi.org/10.1186/s13174-015-0033-5