Fabien Girardin

Leveraging explicitly disclosed location information to understand tourist dynamics: a case study

In recent years, the large deployment of mobile devices has led to a massive increase in the volume of records of where people have been and when they were there. The analysis of these spatio-temporal data can supply high-level human behaviour information valuable to urban planners, local authorities, and designer of location-based services. In this article, we describe our approach to collect and analyse the history of physical presence of tourists from the digital footprints they publicly disclose on the web. Our work takes place in the Province of Florence in Italy, where the insights on the visitors’ flows and on the nationalities of the tourists who do not sleep in town has been limited to information from survey-based hotel and museums frequentation. In fact, most local authorities in the world must face this dearth of data on tourist dynamics. In this case study, we used a corpus of geographically referenced photos taken in the province by 4280 photographers over a period of two years. Based on the disclosure of the location of the photos, we design geovisualisations to reveal the tourist concentration and spatio-temporal flows. Our initial results provide insights on the density of tourists, the points of interests they visit as well as the most common trajectories they follow.

Urban Computing and Mobile Devices

n this issues Works in Progress department, we have 12 urban computing and mobile device entries that span a wide range of computing and social areas. The first entry examines how an urban environment could operate as a large-scale, real-time control system. One project focuses on annotating public spaces and sharing the tags with others. Two projects tie together social networking in cyberspace with local urban communities. Two projects examine computing and social interactions in physical spaces. Two entries explore how to combine synthetic and physical views of urban environments. Four entries investigate how we explore urban spaces, interact with technology in those spaces, and create shared community histories.In this issues Works in Progress department, we have 12 urban computing and mobile device entries that span a wide range of computing and social areas. The first entry examines how an urban environment could operate as a large-scale, real-time control system. One project focuses on annotating public spaces and sharing the tags with others. Two projects tie together social networking in cyberspace with local urban communities. Two projects examine computing and social interactions in physical spaces. Two entries explore how to combine synthetic and physical views of urban environments. Four entries investigate how we explore urban spaces, interact with technology in those spaces, and create shared community histories.

Detecting Air Travel to Survey Passengers on a Worldwide Scale

Market research in the transportation sector is often based on traditional surveys, such as travel diaries, which have well-documented shortcomings and biases. The advent of mobile and wireless technologies enables new methods of investigation of passengers’ behaviour that can eventually provide original insights into mobility studies. Because these technologies can capture travellers’ experience in context and real time, they pave the road for new survey methods. In this article, we demonstrate that mobile phones can recognise air travel with a light algorithm that scans their connectivity to cellular networks. The originality of our method is that it does not rely on any Global Positioning System-like location information and runs on a large variety of mobile phones. It detects flights on a worldwide scale and asks travellers to report on their travel experiences as they occur, eliminating the recall bias of traditional solutions. Once the system detects a journey, it triggers a flight satisfaction questionnaire that sends answers to a centralised server. This approach respects the travellers privacy and proved a 97% success rate in detecting flights in a 12-months study involving six travellers who boarded on 76 planes.

The co-evolution of taxi drivers and their in-car navigation systems

The recent market success of in-car navigation systems creates an opportunity to investigate the appropriation of location-aware systems outside laboratory settings. Through ethnographical lenses, we study how this technology changed the practice of a massive community of its early adopters, the taxi drivers of Barcelona (Spain) and, specifically, their exploitation of pervasive geoinformation. The results show co-evolution: taxi drivers adapt to their in-car navigation systems and adapt them to their needs; in particular, there are evidences of an alteration of the learning processes and of technology appropriation to reduce stress rather than to improve efficiency. We argue that these findings can inform the design of next-generation location-based services.

New tools for studying visitor behaviours in museums: a case study at the Louvre

In this paper we discuss the exploitation of data originated from Bluetooth-enabled devices to understand visitor’s behaviour in the Louvre museum in Paris, France. The collected samples are analysed to examine frequent patterns in visitor’s behaviours, their trajectory, length of stay and some relationships, offering new details on behaviour than previously available. Our work reinforces the emergence of a new methodology to study visitors. It is part of recent lines of investigation that exploit the presence of pervasive data networks to complement more traditional methods in tourism studies, such as surveys based on observation or interviews. However, most past experiments have explored quantitative data coming from mobile phones, GPS, or even geo-tagged user generated content to understand behaviour in a region, or a city, at a larger scale than that of our current work.

Bridging the social-technical gap in location-aware computing

Building ubiquitous applications that exploit location requires integrating underlying infrastructure for linking sensors with high-level representation of the measure space to support human activities. However, the real-world constraints limit the efficiency of location technologies. The inherent spatial uncertainty embedded in mobile and location systems constantly challenges the coexistence of digital and physical spaces. Consequently, the technical mechanisms fail to match the highly flexible, nuanced, and contextual human spatial activities. These discrepancies generate a social-technical gap between what should be socially supported and what can be technically achieved. My research aims at exploring, and hopefully reducing this gap in the context of location-aware computing.