An insight on urban tourism-related phenomena is provided in this study by analysing open and volunteered user generated content. A reference framework method is proposed and applied to an illustrative case study to meet a twofold objective: to identify Tourist Activity Centre – TAC – areas based on their functional character – sightseeing, shopping, eating and nightlife; and, to obtain an up-to-date fine-grain characterization of the most dynamic zones in an urban context. Instasights Heatmaps and data from Location Based Social Networks – Foursquare, Google Places, Twitter and Airbnb – were used to depict tourist urban activity. This reproducible method transcends Instasights generic visualization of popular areas by exploiting the benefits of overlapping LBSN data sources. This method facilitates a granular analysis of tourism-related places of interest and makes headway in bridging the gap between traditional approaches and user preferences, revealed through digital footprints, for urban analysis. The results indicate the potential of this method as a complementary tool for urban planning decision-making.

The sustainability strategy in urban spaces arises from reflecting on how to achieve a more habitable city and is materialized in a series of sustainable transformations aimed at humanizing different environments so that they can be used and enjoyed by everyone without exception and regardless of their ability. Modern communication technologies allow new opportunities to analyze efficiency in the use of urban spaces from several points of view: adequacy of facilities, usability, and social integration capabilities. The research presented in this paper proposes a method to perform an analysis of movement accessibility in sustainable cities based on radio frequency technologies and the ubiquitous computing possibilities of the new Internet of Things paradigm. The proposal can be deployed in both indoor and outdoor environments to check specific locations of a city. Finally, a case study in a controlled context has been simulated to validate the proposal as a pre-deployment step in urban environments.

Despite the improvisations of current urban accessibility regulations and their application in urban systems, it is a fact that our cities are not accessible. Both, the assessment of the effectiveness of urban accessibility and its maintenance over time are issues that require a more consistent approach. In order to address these aspects, it is necessary to have an accurate awareness of the existing condition of urban accessibility. Therefore, the way this information is transformed into specific data, which must be collected, stored and assessed, is one of the main challenges that smart cities face. This research helps implement an integrated system for urban accessibility analysis, combining the latest advances in the Information and Communication Technologies, such as RF & GPS positioning, smart sensing and cloud computing. The main goal of this research is to develop a reliable and effective method to assess public space accessibility with special focus on people with disabilities, by eliciting from users personal experiences. Consequently, the data obtained will enable a better design for improving pedestrian mobility. As a result, a computational architecture for urban dynamics analysis has been designed. Finally, technology and data processing have been validated as an effective system for data collection, and, as a first approach to users’ real experience, it has been proposed to have a testing scenario at the University of Alicante

Social media data has frequently sourced research on topics such as traveller planning or the factors that influence travel decisions. The literature on the location of tourist activities, however, is scarce. The studies in this line that do exist focus mainly on identifying points of interest and rarely on the urban areas that attract tourists. Specifically, as acknowledged in the literature, tourist attractions produce major imbalances with respect to adjacent urban areas. The present study aims to fill this research gap by addressing a twofold objective. The first was to design a methodology allowing to identify the preferred tourist areas based on concentrations of places and activities. The tourist area was delimited using Instasights heatmaps information and the areas of interest were identified by linking data from the location-based social network Foursquare to TripAdvisor’s database. The second objective was to delimit areas of interest based on users’ existing urban dynamics. The method provides a thorough understanding of functional diversity and the location of a city’s different functions. In this way, it contributes to a better understanding of the spatial distribution imbalances of tourist activities. Tourist areas of interest were revealed via the identification of users’ preferences and experiences. A novel methodology was thus created that can be used in the design of future tourism strategies or, indeed, in urban planning. The city of Bucharest, Romania, was taken as a case study to develop this exploratory research.