The international tourism competition poses new challenges to the cruise sector, such as the achievement of the tourists’ satisfaction and the increase in on board comfort. Moreover, the growing sophistication of tourists’ needs leads to a more user-centric touristic offer. Consequently, a personalized cabin environment, which fits the users’ activities and their characteristics, could be a plus value during the cruise vacation. These topics, however, are strictly connected with the diffusion of digital technologies and dynamics, which represent the tools to achieve the goal of a customized on-cruise experience. This paper presents E-Cabin, a novel Internet of Things (IoT) framework architecture that has at its core a reasoning system tuned on data gathered from the environment and from each specific passenger and the activities he/she performs. The framework leverages on knowledge representation with ontologies and consists of a publisher–subscriber communication framework that allows all of the IoT applications to use the reasoner and the provided ontologies. The paper demonstrates the proposed system in a demo cruise cabin where, by using the E-Cabin application, it is possible to set various atmospheres based on the users and activities occurring in the cabin.
Frailty is a clinical condition affecting the elderly population which results in an increased risk of falls. Previous studies demonstrated that falls prevention programs are effective, but they suffer from low adherence, especially when subjects have to train unsupervised in their homes. To try to improve treatment adherence, virtual reality and social media have been proposed as promising strategies for the increase of users’ motivation and thus their willingness to practice. In the context of smart homes, this work presents SocialBike, a virtual reality-based application aimed at improving the clinical outcomes of older frail adults in their houses. Indeed, SocialBike is integrated in the “house of the future” framework and proposes a Dual Task training program in which the users are required to cycle on a stationary bike while recognizing target animals or objects appearing along the way. It also implements the possibility of training with other users, thus reducing the risk of social isolation. Within SocialBike, users can choose the multiplayer mode they prefer (i.e., collaborative or competitive), and are allowed to train following their own attitude. SocialBike’s validation, refinement, and business model are currently under development, and are briefly discussed as future works.
Natural resources are recognized among the key determinants for the improvement of wellness, and thus the development and sustainability of health tourism destinations. This study applied a systematic review to investigate the contributions mapping and analyzing under different perspectives the value of the natural resources of a destination and related activities for health tourism. The main research topics identified from a review of 52 papers include the analysis and exploitation of natural resources in health tourism, the nature-based factors considered in clustering of tourists and their motivations, the development of value offer and marketing, as well as the cultural issues. Research gaps and future directions are summarized in a research agenda laying the foundations for the development of a multidisciplinary research stream focused on nature-based health tourism. Results also represent a key reference for managers and policy makers to identify key issues, areas of intervention and practices for industry development in the health tourism destinations through an effective and sustainable exploitation of natural resources.
New models and technological advances are driving the digital transformation of healthcare systems. Ontologies and Semantic Web have been recognized among the most valuable solutions to manage the massive, various, and complex healthcare data deriving from different sources, thus acting as backbones for ontology-based Decision Support Systems (DSSs). Several contributions in the literature propose Ontology engineering methodologies (OEMs) to assist the formalization and development of ontologies, by providing guidelines on tasks, activities, and stakeholders’ participation. Nevertheless, existing OEMs differ widely according to their approach, and often lack of sufficient details to support ontology engineers. This paper performs a meta-review of the main criteria adopted for assessing OEMs, and major issues and shortcomings identified in existing methodologies. The key issues requiring specific attention (i.e., the delivery of a feasibility study, the introduction of project management processes, the support for reuse, and the involvement of stakeholders) are then explored into three use cases of semantic-based DSS in health-related fields. Results contribute to the literature on OEMs by providing insights on specific tools and approaches to be used when tackling these issues in the development of collaborative OEMs supporting DSS.
Business traveling is attracting growing attention due to the expansion of international markets. This fact calls for an increasing attention of the tourism sector toward the needs of business travellers, who often require services that are different from the ones desired by leisure tourists. The application of smart solutions coming from Context Awareness and Ambient Intelligence aimed at promoting guests' comfort and well-being, also in cases in which they have special needs, represents a promising solution to tackle business travellers' requirements and thus, to increase hotels attractiveness and incomes. In this context, this work introduces RoomFort, a smart comfort management system aimed at enhancing comfort of hotel room guests and leveraging on semantic representations of comfort, environment, and sensors. RoomFort provides a set of domain ontologies to formalize comfort-related metrics and to exploit the automatic reasoning capabilities provided by Semantic Web technologies, while gathering data through a network of sensors to ensure guests are provided with tailored comfort profiles during their stays in the hotel. Particular focus has been placed on visual comfort, since indoor lighting features constitute one of the main factors influencing the two main activities that most business travellers accomplish in their hotel room: working and relaxing.
Researches in the field of ambient assisted living (AAL) have increased in the last ten years, and the paradigms of the smart home have widely spread. Smart homes must consider the health-related issues and the real needs deriving from the ageing of their dwellers. In the smart home, appliances are expected to provide support to the residents, especially when they are characterized by disabilities and/or impairments related to ageing. While most of the AAL solutions presented in literature rely on complex systems and architectures, residents affected by mild or moderate disabilities can take advantage of just a simpler reconfiguration of living environments, i.e., the replacement of certain appliances with others that are able to help them in coping with their limitations. This paper proposes a semantic-based decision support system (DSS), which relies on ontological models, to assist designers in domestic environments’ reconfiguration. The ontology leverages semantic representations of dwellers and domestic environments’ domains of knowledge to foster the adoption of appliances able to help the residents to live independently. The development process of the ontology is presented in detail together with the results deriving from reasoning processes. To ease the reconfiguration of domestic environments, a prototypical application taking advantage of the DSS is presented.
This work introduces ComfOnt, a semantic framework developed within the context of ambient assisted living, context awareness, and ambient intelligence Italian research projects. ComfOnt leverages knowledge regarding Smart Home inhabitants and their particular needs, the devices deployed inside the domestic environment (appliances, sensors, and actuators), the amount of their energy consumption, and indoor comfort metrics to provide dwellers with customized services. Developed reusing widely adopted ontologies, ComfOnt aims at providing inhabitants with the possibility of having personalized indoor comfort in their living environments and at helping them in scheduling their daily activities requiring appliances; in fact, the proposed semantic framework enables the representation of appliances' energy consumption and the energy profile of the Smart Home, thus assisting the dwellers in avoiding power cuts and fostering energy savings. ComfOnt serves as a knowledge base for a prototypical application (DECAM) dedicated to Smart Home inhabitants; the architecture and the functionalities of DECAM are here presented.Although research in the fields of SH, ambient assisted living (AAL), ambient intelligence (AmI), context awareness (CA), and IoT leveraging semantic formalization of knowledge has acquired a growing importance in the last years, only a few works dedicated to the SH tackled the issue of modeling indoor comfort metrics. This work aims at contributing to the field of domain ontologies dedicated to the representation of knowledge necessary to customize services within an SH, including comfort metrics leveraging on already existing models. The proposed set of domain ontologies arises from the experiences of three Italian research projects funded by the Lombardy Region: i-Zeb, Future Homes for Future Communities (FHfFC), and CasAware. i-Zeb [4] is a project aimed at researching and investigating the use of innovative building materials and technological solutions to foster the implementation of Nearly Zero-Energy Buildings. FHfFC [5] focuses on deploying a semantic architecture to enable a set of assistive services aimed at improving inhabitants' daily lives; the services are addressed to an ageing population and encompass a wide range of fields, such as indoor comfort, device interoperability, and domestic rehabilitation. CasAware [6,7] leverages ontological representation of domestic appliances and their energy consumption to foster energy saving behavior, help the dwellers to better schedule their operations with appliances, and avoid domestic power cuts.The set of domain ontologies developed within these three projects-named ComfOnt-allows the formalization of some fundamental indoor comfort metrics, including Italian regulations and laws, and knowledge regarding sensors, actuators, and measurements; ComfOnt can be adopted to describe environmental conditions within the SH and to trigger comfort actuation after detecting an unsafe or uncomfortable situation, exploiting the results deriving from reasoning proc...
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