Retrieval of similar travel routes using GPS tracklog place names

GPS tracklogs provide a valuable record of routes travelled. In this paper we describe initial experiments exploring the use of text information retrieval techniques for the location of similar trips from within a GPS tracklog. We performed the experiment on a dataset of 528 individual trips gathered over a seven month time period from a single user. The results of our preliminary study suggest that traditional text-based information retrieval techniques can indeed be used to locate similar and related tracklogs

How would tourists use Green Spaces? Case Studies in Lisbon

EntretextosThis report provides in a relative condensed format the results of small-scale study undertaken in Lisbon during the Meeting of the CyberParks Project (www.cost.eu/COST_Actions/tud/Actions/TU1306). CyberParks is a COST Action coordinated by the Universidade Lusófona at the CeiED - Interdisciplinary Research Centre for Education and Development. The Project aims at creating a research platform on the relationship between Information and Communication Technologies (ICT) and the production of public open spaces, and their relevance to sustainable urban development. The impacts of this relationship are being explored from social, ecological, urban design and technological perspectives. Based on the supposition that the participants of the Meeting are tourists visiting Lisbon, a survey was carried out on the topic how people actually use and how they would use public spaces. This survey is also the first approach to the case study areas chosen in Lisbon: Parque Quinta das Conchas and Jardim da Estrela. Both green spaces will be subject of further studies in the forthcoming years. This study employed (1) a questionnaire for measuring the user’s experience and preferences, and (2) two different tracking devices that utilise GNSS (Global Navigation Satellite Systems), in our case the GPS for satellite positioning technologies. It also presents the results of a study on the relevance of wi-fi in Lisbon’s public spaces. Even considering that the surveys in Lisbon’s green spaces are a first exercise within the work programme of CyberParks they show important outcomes. On the one hand, regarding the technologies used and their potential for research and on the other hand the findings about Lisbon’s green spaces. It should be noted that the conducted surveys and the gathered data are statistically not representative, but can be characterised as an empirical case and as a showcase, as how tourists tend to use a green space. The results shows that surveys benefit from multiple research methods and from combining insights.Este relatório apresenta, em formato condensado, os resultados de um estudo de pequena escala realizado em Lisboa durante o Seminário do Projeto CyberParks. CyberParks é uma Ação COST coordenada pela Universidade Lusófona/CeiED - Centro de Estudos Interdisciplinares em Educação e Desenvolvimento. O projeto visa a criação de uma plataforma de debate sobre a relação entre as Tecnologias de Informação e Comunicação (TIC) e a produção de espaços públicos, e da sua relevância para o desenvolvimento urbano sustentável. Os impactos dessa relação estão a ser explorados a partir de perspetivas sociais, ecológicas, tecnológicas e de desenho urbano. Na sua etapa exploratória, este estudo assenta na suposição de que os participantes do Seminário são turistas de visita a Lisboa. A partir dos dados recolhidos pelos investigadores envolvidos na ação COST, foi realizada uma análise à forma como diferentes indivíduos usam, e como poderão usar, diferentes espaços públicos verdes. Este estudo apresenta, portanto, a primeira abordagem às áreas de estudos selecionadas em Lisboa. São elas o Parque Quinta das Conchas e o Jardim da Estrela. Ambos os espaços verdes serão objeto de novos estudos nos próximos anos. Neste primeiro estudo exploratório foram empregues: (1) um questionário, para aferir a experiência de um potencial utilizador e as suas preferências, e (2) dois dispositivos diferentes de rastreamento que utilizam tecnologia GNSS (Sistemas de Navegação Global por Satélite) e, no nosso caso, o GPS para as tecnologias de posicionamento por satélite. Ele também apresenta os resultados de um estudo realizado sobre a relevância do wi-fi em espaços públicos na cidade de Lisboa. Mesmo considerando que os estudos realizados nos espaços verdes representam um primeiro exercício no âmbito do programa de trabalho do CyberParks em Lisboa, são aqui revelados resultados importantes. Por um lado, o recurso às tecnologias utilizadas e seu potencial para a investigação e, por outro lado, os resultados sobre a vivência dos espaços verdes. Deve-se notar que os dados recolhidos não são estatisticamente representativos, mas evidenciam um caso empírico de como turistas tendem a usar um espaço verde urbano. A combinação do questionário com novos métodos digitais resultou num grande ganho de conhecimento, recobrindo as áreas de estudo sob a perspetiva de um turista, para além de maiores informações sobre as potencialidades e limites da tecnologia digital como ferramenta de investigação. Os resultados mostram que a investigação no campo social pode se beneficiar da combinação de vários métodos e técnicas

PinMe: Tracking a Smartphone User around the World

With the pervasive use of smartphones that sense, collect, and process valuable information about the environment, ensuring location privacy has become one of the most important concerns in the modern age. A few recent research studies discuss the feasibility of processing data gathered by a smartphone to locate the phone's owner, even when the user does not intend to share his location information, e.g., when the Global Positioning System (GPS) is off. Previous research efforts rely on at least one of the two following fundamental requirements, which significantly limit the ability of the adversary: (i) the attacker must accurately know either the user's initial location or the set of routes through which the user travels and/or (ii) the attacker must measure a set of features, e.g., the device's acceleration, for potential routes in advance and construct a training dataset. In this paper, we demonstrate that neither of the above-mentioned requirements is essential for compromising the user's location privacy. We describe PinMe, a novel user-location mechanism that exploits non-sensory/sensory data stored on the smartphone, e.g., the environment's air pressure, along with publicly-available auxiliary information, e.g., elevation maps, to estimate the user's location when all location services, e.g., GPS, are turned off.Comment: This is the preprint version: the paper has been published in IEEE Trans. Multi-Scale Computing Systems, DOI: 0.1109/TMSCS.2017.275146

MobGeoSen: facilitating personal geosensor data collection and visualization using mobile phones

Mobile sensing and mapping applications are becoming more prevalent because sensing hardware is becoming more portable and more affordable. However, most of the hardware uses small numbers of fixed sensors that report and share multiple sets of environmental data which raises privacy concerns. Instead, these systems can be decentralized and managed by individuals in their public and private spaces. This paper describes a robust system called MobGeoSens which enables individuals to monitor their local environment (e.g. pollution and temperature) and their private spaces (e.g. activities and health) by using mobile phones in their day to day life

Reflecting Human Knowledge of Place and Route-Choice Behavior Using Big Data

Exploring human knowledge of geographical space and related behavior not only helps in understanding human-environment interactions and dynamic geographic processes, but also advances Geographic Information Systems (GIS) toward a human-centric paradigm to make daily life more efficient. Today’s relatively easy acquisition of various big data provides an unprecedented opportunity for geographers to answer research questions that previously could not be adequately addressed. However, new challenges also arise regarding data quality and bias as well as change in methodology for dealing with big data that are different from traditional data types. Representing people’s perception of place and studying driver’s route-choice behavior are two of the many applications of big data in answering research questions about human knowledge and behavior in the fields of GIS and transportation. Incorporating three papers, this dissertation focuses on these two different applications to achieve the following objectives: 1) examine the degree to which a geographic place’s spatial extent can be estimated from human-generated geotagged photos; 2) address the challenge of geotagged photos’ uneven spatial distribution in place estimation and explore an approach that can better derive a place’s spatial extent; 3) develop a method that can properly estimate the spatial extent of a place that has multiple disjoint regions while considering geotagged photos’ uneven distribution; 4) explore useful spatiotemporal patterns of taxi drivers’ route-choice behavior in a dynamic urban environment. This dissertation makes three major contributions to big data applications’ systematic theory: 1) proposes an effective approach to handling the uneven spatial distribution problem of geotagged photos as a type of volunteered geographic data by modeling their representativeness; 2) develops methods that can properly derive the vague spatial extent of a place with or without disjoint regions; and 3) explores taxi drivers’ route-choice patterns in different situations that can inform future transportation decisions and policy-making processes

The Shortest Path to Happiness: Recommending Beautiful, Quiet, and Happy Routes in the City

When providing directions to a place, web and mobile mapping services are all able to suggest the shortest route. The goal of this work is to automatically suggest routes that are not only short but also emotionally pleasant. To quantify the extent to which urban locations are pleasant, we use data from a crowd-sourcing platform that shows two street scenes in London (out of hundreds), and a user votes on which one looks more beautiful, quiet, and happy. We consider votes from more than 3.3K individuals and translate them into quantitative measures of location perceptions. We arrange those locations into a graph upon which we learn pleasant routes. Based on a quantitative validation, we find that, compared to the shortest routes, the recommended ones add just a few extra walking minutes and are indeed perceived to be more beautiful, quiet, and happy. To test the generality of our approach, we consider Flickr metadata of more than 3.7M pictures in London and 1.3M in Boston, compute proxies for the crowdsourced beauty dimension (the one for which we have collected the most votes), and evaluate those proxies with 30 participants in London and 54 in Boston. These participants have not only rated our recommendations but have also carefully motivated their choices, providing insights for future work.Comment: 11 pages, 7 figures, Proceedings of ACM Hypertext 201