KDD

Understanding the spatiotemporal distribution of people within a city is crucial to many planning applications. Obtaining data to create required knowledge, currently involves costly survey methods. At the same time ubiquitous mobile sensors from ...

Commuting matrices are key for a variety of fields, including transportation engineering and urban planning. Up to now, these matrices have been typically generated from data obtained from surveys. Nevertheless, such approaches typically involve high ...

The huge quantity of positioning data registered by our mobile phones stimulates several research questions, mainly originating from the combination of this huge quantity of data with the extreme heterogeneity of the tracked user and the low granularity ...

Human activity behaviors in urban areas mostly occur in interior places, such as department stores, office buildings, and museums. Understanding and characterizing human spatio-temporal interactive behaviors in these indoor areas can help us evaluate ...

Using sensor data from fixed highway traffic detectors, as well as data from highway patrol logs and local weather stations, we aim to answer the domain problem: "A traffic incident just occurred. How severe will its impact be?" In this paper we show a ...

This paper explores the smart city concept and proposes an innovative way of sensing urban places' life using aggregation of devices sensors (cameras...) and human sensors (VGI, geosocial networks) datasets. The paper also discusses the need of an ...

This paper introduces a micro-simulation of urban traffic flows within a large scale scenario implemented for the Greater Dublin region in Ireland. Traditionally, the data available for traffic simulations come from a population census and dedicated ...

Location-based services allow users to perform geo-spatial check-in actions, which facilitates the mining of the moving activities of human beings. This paper proposes to recommend time-sensitive trip routes, consisting of a sequence of locations with ...

In recent years, researches on recommendation of urban Points-Of-Interest (POI), such as restaurants, based on social information have attracted a lot of attention. Although a number of social-based recommendation techniques have been proposed in the ...

Compared with traditional itinerary planning, intention oriented itinerary recommendation can provide more flexible activity planning without the user pre-determined destinations and is specially helpful for those strangers in unfamiliar environment. ...

The widely use of GPS-enabled devices has provided us amount of trajectories related to individuals' activities. This gives us an opportunity to learn more about the users' daily lives and offer optimized suggestions to improve people's trip styles. In ...

A basic task of urban mobility management is the real-time monitoring of traffic within key areas of the territory, such as main entrances to the city, important attractors and possible bottlenecks. Some of them are well known areas, while while others ...

Urban geographers, planners, and economists have long been studying urban spatial structure to understand the development of cities. Statistical and data mining techniques, as proposed in this paper, go a long way in improving our knowledge about human ...

Trajectory similarity search studies the problem of finding a trajectory from the database such the found trajectory most similar to the query trajectory. Past research mainly focused on two aspects: shape similarity search and semantic similarity ...

We introduce our vision for mining fine-grained urban traffic knowledge from mobile sensing, especially GPS location traces. Beyond characterizing human mobility patterns and measuring traffic congestion, we show how mobile sensing can also reveal ...

To enable smart transportation, a large volume of vehicular GPS trajectory data has been collected in the metropolitan-scale Shanghai Grid project. The collected raw GPS data, however, suffers from various errors. Thus, it is inappropriate to use the ...

The confluence of several developments has created an opportune moment for energy system modernization. In the past decade, smart grids have attracted many research activities in different domains. To realize the next generation of smart grids, we must ...

For people travelling using public transport, overcrowding is one of the major causes of discomfort. However, most Advanced Traveller Information Systems (ATIS) do not take crowdedness into account, suggesting routes either based on number of ...

Rapid tranit systems are the most important public transportation service modes in many large cities around the world. Hence, its service reliability is of high importance for government and transit agencies. Despite taking all the necessary precautions,...

People often have the demand to decide where to wait for a taxi in order to save their time. In this paper, to address this problem, we employ the non-homogeneous Poisson process (NHPP) to model the behavior of vacant taxis. According to the statistics ...

Outlier detection in large-scale taxi trip records has imposed significant technical challenges due to huge data volumes and complex semantics. In this paper, we report our preliminary work on detecting outliers from 166 millions taxi trips in the New ...

Volumes of urban sensing data captured by consumer electronic devices are growing exponentially and current disk-resident database systems are becoming increasingly incapable of handling such large-scale data efficiently. In this paper, we report our ...