Mobile pervasive augmented reality systems the role of user preferences in perceived quality of experience

This work addresses reasons and aspects required to boost the acceptance and use of mobile pervasive augmented reality systems - MPARS - for outdoor applications and the need to develop context-aware close to- real-time feedback mechanisms that take into consideration a continuous measurement of Quality of Experience. For this purpose, we delve into how user preferences can be integrated in context-aware feedback systems, proposing a Quality of Experience theoretical model derived from an analysis on technology adoption models and user preferences. The how and why such model can be integrated into future solutions is also addressed.info:eu-repo/semantics/acceptedVersio

The Collaborative Economy through the Lens of Sustainable Tourism. A Regional-Centric View

Nowadays the tourism industry faces major changes given the vast possibilities for the development of a collaborative economy in tourism that brings forth a new marketplace where consumers rely on each other -changing renting, swapping, and sharing their accommodation locations. The purpose of the present paper is to answer one of the most important challenges of the City of Brașov in Romania, which is the management of the touristic offer. The paper provides a quantitative-qualitative research approach that analyzes - based on semi-structured surveys with the users of collaborative platforms - the perception of travelers concerning the development of collaborative tourism in Brasov County. The management of touristic offer should take into account the pressure that this new type of renting may be exerting on the local economy, especially considering unfair competition on other segments of the tourist market and the change in the physiognomy of the cities of Brașov County

The Evolution of First Person Vision Methods: A Survey

The emergence of new wearable technologies such as action cameras and smart-glasses has increased the interest of computer vision scientists in the First Person perspective. Nowadays, this field is attracting attention and investments of companies aiming to develop commercial devices with First Person Vision recording capabilities. Due to this interest, an increasing demand of methods to process these videos, possibly in real-time, is expected. Current approaches present a particular combinations of different image features and quantitative methods to accomplish specific objectives like object detection, activity recognition, user machine interaction and so on. This paper summarizes the evolution of the state of the art in First Person Vision video analysis between 1997 and 2014, highlighting, among others, most commonly used features, methods, challenges and opportunities within the field.Comment: First Person Vision, Egocentric Vision, Wearable Devices, Smart Glasses, Computer Vision, Video Analytics, Human-machine Interactio

Rethinking tourism destinations: collaborative network models for the tourist 2.0

In the increasingly saturated tourism market, an effective tourism destination management is essential to support competitive and sustainable growth. The topic becomes interesting in light of the spread of the collaborative network (CN) organisational models and the massive diffusion of web 2.0 and mobile technology. The formers have proven to give concrete opportunities of development in many industrial sectors, the latter has been changing the way tourists experience a destination. Even if several case studies of CNs in tourism are known, a comprehensive study of how tourism destinations can benefit of CN models and enabling technologies is not present; especially in the effort to help tourism destinations in setting up services able to actively support each phase of the tourist 2.0 lifecycle. In this paper we highlight how CN models are able to support the tourism destination management in order to gain competitiveness for local areas, to improve flexibility in services provision and to give tourists the possibility to live an augmented tourism experience. Furthermore, a review of the most suitable forms of collaborative network for tourism destination and their ways to actively support the augmented experience of the tourist 2.0 are proposed

Social and Semantic Contexts in Tourist Mobile Applications

The ongoing growth of the World Wide Web along with the increase possibility of access information through a variety of devices in mobility, has defi nitely changed the way users acquire, create, and personalize information, pushing innovative strategies for annotating and organizing it. In this scenario, Social Annotation Systems have quickly gained a huge popularity, introducing millions of metadata on di fferent Web resources following a bottom-up approach, generating free and democratic mechanisms of classi cation, namely folksonomies. Moving away from hierarchical classi cation schemas, folksonomies represent also a meaningful mean for identifying similarities among users, resources and tags. At any rate, they suff er from several limitations, such as the lack of specialized tools devoted to manage, modify, customize and visualize them as well as the lack of an explicit semantic, making di fficult for users to bene fit from them eff ectively. Despite appealing promises of Semantic Web technologies, which were intended to explicitly formalize the knowledge within a particular domain in a top-down manner, in order to perform intelligent integration and reasoning on it, they are still far from reach their objectives, due to di fficulties in knowledge acquisition and annotation bottleneck. The main contribution of this dissertation consists in modeling a novel conceptual framework that exploits both social and semantic contextual dimensions, focusing on the domain of tourism and cultural heritage. The primary aim of our assessment is to evaluate the overall user satisfaction and the perceived quality in use thanks to two concrete case studies. Firstly, we concentrate our attention on contextual information and navigation, and on authoring tool; secondly, we provide a semantic mapping of tags of the system folksonomy, contrasted and compared to the expert users' classi cation, allowing a bridge between social and semantic knowledge according to its constantly mutual growth. The performed user evaluations analyses results are promising, reporting a high level of agreement on the perceived quality in use of both the applications and of the speci c analyzed features, demonstrating that a social-semantic contextual model improves the general users' satisfactio

Synergistic user ↔ context analytics

Various flavours of a new research field on (socio-)physical or personal analytics have emerged, with the goal of deriving semanticallyrich insights from people’s low-level physical sensing combined with their (online) social interactions. In this paper, we argue for more comprehensive data sources, including environmental and application-specific data, to better capture the interactions between users and their context, in addition to those among users. We provide some example use cases and present our ongoing work towards a synergistic analytics platform: a testbed based on mobile crowdsensing and IoT, a data model for representing the different sources of data and their connections, and a prediction engine for analyzing the data and producing insights

Sustainable Mobility for Island Destinations

This open access book presents the findings of the CIVITAS DESTINATIONS project regarding the link between mobility and tourism in urban areas and the complications tourist destinations face in becoming more sustainable. It integrates the tourist mobility needs and the associated fluctuation impacts in the design of mobility solutions in order to enforce the accessibility, attractiveness, efficiency and sustainability of transport services and infrastructure for both residents and tourists in island cities such as Rethymno, Crete, and Valetta, Malta. Sustainable Mobility for Island Destinations contains contributions from highly experienced academics, engineers, and planners in the area of sustainable tourism, mobility services, and smart solutions design companies assisting: the change of the mind set in insular and tourism areas; the adoption of green mobility systems and services; and monitoring the environmental benefits to assist towards the Climate Change. It explores the challenges tourist islands face, such as the seasonal fluxes in transport usage, the pressures of tourism to provide aesthetic green spaces, and the space issues of being an island in relation to economic potential and infrastructure construction. The book suggests areas for future research, and implementation of innovative systems and policies. It will be of interest to academics, planners, decision makers, and environmentalists

Google popular times : towards a better understanding of tourist customer patronage behavior

This paper aims to investigate actual tourist customer visiting behavior with behavioral data from Google Popular Times to evaluate the extent that such an online source is useful to better understand, analyze, and predict tourist consumer behaviors. Following six hypotheses on tourist behavior, a purpose-built software tool was developed, pre-tested, and then used to obtain a large-scale data sample of 20,000 time periods for 198 restaurants. Both bi-variate linear regression and correlation analyses were used for hypothesis testing. Support was established for the hypotheses, through an analysis of customer reviews, timing effects, the number of pictures uploaded, and price segment information provided by tourists to a given restaurant. Also, a relationship to average duration time was found to be positive. The findings demonstrate that data provided through Google Popular Times matches theoretical and logical assumptions to a high degree. Thus, the data source is potentially powerful for providing valuable information to stakeholders (e.g., researchers, managers, tourists). This paper is the first to both conceptually and empirically demonstrate the practicality and value of Google Popular Times to better understand, analyze, and predict tourist consumer behaviors. Value is thereby provided by the potential for this approach to offer insights based behavioral data. Importantly, until now such an approach to gathering and analyzing this volume of actual customer data was previously considered far less practical in terms of time and expense