Any virtual environment (VE) built in a classical way is dedicated to a very specific domain. Its modification or even adaptation to another domain requires an expensive human intervention measured in time and money. This way, the product, that means the VE, returns at the first phases of the development process. In a previous work we proposed an approach that combines domain ontologies and conceptual modeling to construct more accurate VEs. Our method is based on the description of the domain knowledge in a standard format and the assisted creation (using these pieces of knowledge) of the VE. This permits the explanation within the virtual reality (VR) simulation of the semantic of the whole context and of each object. This knowledge may be then transferred to the public users. In this paper we prove the effectiveness of our method on the construction process of an VE that simulates the organization of a Greek-Roman colony situated on the Black Sea coast and the economic and social activities of its people

In the context of hyper-connected cars and a growing heterogeneous digital ecosystem, we wish to make the most of the data available from the various sensors, devices and services that compose the ecosystem, in order to propose a proof of concept in-vehicle system that enhances the driving experience. We focus on improving the driving experience along three main directions, namely: (1) driving and trip planning, (2) health and well-being and (3) social and online activities. We approached the in-vehicle space as a smart interface to the intelligent driving environment. The digital data-producers in the ecosystem of the connected car are sources of raw data of various categories, such as data from the outside world, gathered from sensors or online services, data from the car itself and data from the driver gathered with various mobile and wearable devices, by means of observing his state and by means of his social media and online activity. Data is later processed into three information categories—driving, wellness, and social—and used to provide multi-modal interaction, namely visual, audio and gesture. The system is implemented to act in response to the trafficked information on different levels of autonomy, either in a reactive manner, by simple monitoring, or in a proactive manner. The system is designed to provide an in-vehicle system that assists the driver with planning the travel (Drive panel), by providing a comfortable environment for the driver while monitoring him (Wellness panel), and by adaptively managing interactions with their phone and the digital environment (Social panel). Heuristic evaluation of the system is performed, with respect to guidelines formulated for automated vehicles, and a SWOT analysis of the system is also presented in the paper.

Haptics is the science of merging tactile sensation with computer applications, thereby enabling users to receive feedback they can feel (in addition to auditory and visual cues). Multimodal environments where visual, auditory and haptic stimuli are present convey information more efficiently since the user manipulates and experiences the environment through multiple sensory channels. The availability of haptic systems enables the augmentation of traditional instruction with interactive interfaces offering enhanced motivation and intellectual stimulation. Although the haptic devices have not made large in roads into education, we believe that the potential for revolutionary change now exists due to the recent availability of both the hardware and software components. This paper brings into discussion some of the most relevant technological issues involving haptic systems in education. One of these issues is choosing the suitable haptic hardware, API or framework for developing a visuo-haptic e-Learning system. The decision is based on several criteria such as multimodal resources needed by the software system, compatibility with haptic devices, dynamic configuration of the scene, and so on. Another issue is related to the software system reactivity at the user actions. The immediate haptic feedback from virtual models, together with the synchronisation of haptic and visual cues generated by computer to its users are essential for enhancing the user's learning path. Providing realistic visuo-haptic models as much as it is possible is also another problem that the development of the haptic e-learning system should deal with. Such models help to obtain accurate training scenarios developed for the teaching, for example, of medical protocols, or chemical or physical processes.