Advanced Driver Assistant systems (ADAS) are receiving increased research focus as they promote a safer and more comfortable driving experience. In this context, personalization can play a key role as the different driver/rider needs, the environmental context and driver’s/rider’s state can be taken into account towards delivering custom tailored interaction and performing intelligent decision making. This paper presents an ontology-based approach for personalizing Human Machine Interaction (HMI) elements in ADAS systems. The main features of the presented research work include: (a) semantic modelling of relevant data in the form of an ontology meta-model that includes the driver/ rider information, the vehicle and its HMI elements, as well as the external environment, (b) rule-based reasoning on top of the meta-model to derive appropriate personalization decisions, and (c) adaptation of the vehicle’s HMI elements and interaction paradigms to best fit the particular driver or rider, as well as the overall driving context.

The population of elderly people and disabled has exponentially increased thanks to advances of medicine which allow people to live longer and healthier than the previous generations. In this context, Ambient Assisted Living (AAL) applications which promotes independent living is more necessary than ever. Also, the Internet of Things (IoT) proliferates as the dominant technological paradigm for the open deployment of networked smart objects in the environment, including physical things, smart devices and entire applications. In our work, a primary objective was the delivery of an AAL framework on the top of smart objects which uses the full range of IoT technologies. Very early, it became evident that the demand of personalized applications in the context of AAL is very intense. This is mainly due to the highly individualized and fluid nature of the required applications. Along these lines, we focus in providing an end-user programming environment to empower carers, possibly the elderly and family themselves, with the necessary tools to easily and quickly craft, test, modify and deploy smart object applications they would like to have in their everyday life. In this paper, we support personalized automations using smart objects for outdoor daily activities, outside the elderly's protected home environment. We initially outline possible useful mobility scenarios. Then, we elaborate on the visual tools we are developing, followed by a brief case study using them.

This paper discusses technology acceptance in the context of Ambient Intelligence (AmI) environments. Determining what would make a technology acceptable by users was widely recognized as a significant field of research since the seventies. Ever since several models have been developed, while recent advances in technology have led to increased research interest in assessing technology acceptance in a variety of domains. This has resulted in a plethora of studies and an extensive number of parameters that can be considered important towards predicting the acceptance of a given technology by its target audience. An important concern is how to practically employ these models for the assessment of AmI environments, given their high complexity and the wide range of potential contexts and target users. To this end, this paper carries out a review of the most important models and their evolution over time, as well as a review of studies extending these models in a variety of domains beyond the workplace. Furthermore, a classification of the parameters studied across these models is carried out, identifying a common feature across existing technology acceptance studies, namely that all assessments are based on self-reported metrics. This highlights the need for a synergistic evaluation approach, where assessment will move beyond self-reported or observed metrics and will be supported and assisted by the AmI environment itself.

The case of mixed-reality projector-camera systems is considered and, in particular, those which employ hand-held boards as interactive displays. This work focuses upon the accurate, robust, and timely detection and pose estimation of such boards, to achieve high-quality augmentation and interaction. The proposed approach operates a camera in the near infrared spectrum to filter out the optical projection from the sensory input. However, the monochromaticity of input restricts the use of color for the detection of boards. In this context, two methods are proposed. The first regards the pose estimation of boards which, being computationally demanding and frequently used by the system, is highly parallelized. The second uses this pose estimation method to detect and track boards, being efficient in the use of computational resources so that accurate results are provided in real-time. Accurate pose estimation facilitates touch detection upon designated areas on the boards and high-quality projection of visual content upon boards. An implementation of the proposed approach is extensively and quantitatively evaluated, as to its accuracy and efficiency. This evaluation, along with usability and pilot application investigations, indicate the suitability of the proposed approach for use in interactive, mixed-reality applications.

Ambient Assisted Living (AAL) promotes independent living, while the Internet of Things (IoT) proliferates as the dominant technology for the deployment of pervasive smart objects. In this work, we focus on the delivery of an AAL framework utilizing IoT technologies, while addressing the demand for very customized automations due to the diverse and fluid (can change over time) user requirements. The latter turns the idea of a general-purpose application suite to fit all users mostly unrealistic and suboptimal. Driven by the popularity of visual programming tools, especially for children, we focused in directly enabling end-users, including carers, family or friends, even the elderly/disabled themselves, to easily craft and modify custom automations. In this paper we firstly discuss scenarios of highly personalized AAL automations through smart objects, and then elaborate on the capabilities of the visual tools we are currently developing on a basis of a brief case study.

This paper reports on ongoing work regarding interactive 3D visualization of large scale data centres in the context of Big Data and data centre infrastructure management. The proposed approach renders a virtual area of real data centres preserving the actual arrangement of their servers and visualizes their current state while it notifies users for potential server anomalies. The visualization includes several condition indicators, updated in real time, as well as a color-coding scheme for the current servers’ condition referring to a scale from normal to critical. Furthermore, the system supports on demand exploration of an individual server providing detailed information about its condition, for a specific timespan, combining historical analysis of previous values and the prediction of potential future state. Additionally, natural interaction through hand-gestures is supported for 3D navigation and item selection, based on a computer-vision approach.

Two dimensional paintings were exhibited in museums and art galleries in the same manner since at least three centuries. However, the emergence of novel interactive technologies provides the opportunity to change this status quo. By 2006, according to the Institute for Museum and Library Services, 43 % of museum visits in the U.S. were remote. According to the Institute for the Future, “Emerging technologies are transforming everything that constitutes our notion of “reality” – our ability to sense our surroundings, our capacity to reason, our perception of the world”. In the present age, that technology is becoming mixed to the fabric of reality to offer novel experiences in Cultural Heritage Institutions. This work presents the design and implementation of a technological framework based on ambient intelligence to enhance visitor experiences within Heritage Institutions by augmenting two dimensional paintings. Among the major contributions of this chapter is the support of personalized multi user access to exhibits, facilitating also adaptation mechanisms for altering the interaction style and content based on the requirements of each Heritage Institution’s visitor. A standards compliant knowledge representation and the appropriate authoring tools guarantee the effective integration of this approach in any relevant context. The developed applications have been deployed within a simulation space of the FORTH-ICS AmI facility and evaluated by users in the context of a pilot study.

Adaptation and content personalization in the context of multi user museum exhibits Conference Paper · June 2016 with 2 Reads Conference: 1st Workshop on Advanced Visual Interfaces for Cultural Heritage co-located with the International Working Conference on Advanced Visual Interfaces (AVI 2016), At Bari, Italy 1st Nikolaos Partarakis 4.18 · Foundation for Research and Technology - Hellas 2nd Margherita Antona 15.64 · Foundation for Research and Technology - Hellas 3rd Emmanouil Zidianakis 1.71 · Foundation for Research and Technology - Hellas 4th Constantine Stephanidis Abstract Two dimensional paintings are exhibited in museums and art galleries in the same manner since at least three centuries. However, the emergence of novel interaction techniques and metaphors provides the opportunity to change this status quo, by supporting mixing physical and digital Cultural Heritage experiences. This paper presents the design and implementation of a technological framework based on Ambient Intelligence to enhance visitor experiences within Cultural Heritage Institutions (CHIs) by augmenting two dimensional paintings. Among the major contributions of this research work is the support of personalized multi user access to exhibits, facilitating also adaptation mechanisms for altering the interaction style and content to the requirements of each CHI visitor. A standards compliant knowledge representation and the appropriate authoring tools guarantee the effective integration of this approach to the CHI context.

Augmented reality fitting rooms enrich customers’ experience and expedite the shopping procedure. This paper presents an Augmented Reality (AR) mirror which provides motion-based interaction to the users and suggests various outfits. The proposed system can be easily installed inside or at the window of a retail shop, enabling the users to stand in front of it and see themselves wearing clothes that the system suggests while they are able to naturally interact with the system remotely, using gestures, in order to like or dislike the recommended outfit. The users can also choose to post photos wearing the proposed clothes on their social media accounts, as well as to buy the clothes either directly from the store or on-line.