2013 Proceeding- General Chairs:
- Steven E. Koonin,
- Ouri E. Wolfson,
- Program Chair:
- Yu Zheng
Urbanization's rapid progress has led to many big cities, which have modernized people's lives but also engendered big challenges, such as air pollution, increased energy consumption and traffic congestion. Tackling these challenges can seem nearly impossible years ago given the complex and dynamic settings of cities. Nowadays, sensing technologies and large-scale computing infrastructures have produced a variety of big data in urban spaces, e.g. human mobility, air quality, traffic patterns, and geographical data. The big data implies rich knowledge about a city and can help tackle these challenges when used correctly. Urban computing is a process of acquisition, integration, and analysis of big and heterogeneous data generated by a diversity of sources in urban spaces, such as sensors, devices, vehicles, buildings, and human, to tackle the major issues that cities face, e.g. air pollution, increased energy consumption and traffic congestion. Urban computing connects unobtrusive and ubiquitous sensing technologies, advanced data management and analytics models, and novel visualization methods, to create win-win-win solutions that improve urban environment, human life quality, and city operation systems. Urban computing also helps us understand the nature of urban phenomena and even predict the future of cities.
Proceeding Downloads
Exploring human movements in Singapore: a comparative analysis based on mobile phone and taxicab usages
Existing studies extensively utilized taxicab trips and individuals' movements captured by mobile phone usages (referred as "mobile phone movements" hereafter) to understand human mobility patterns in an area. However, all these studies analyze taxicab ...
A review of urban computing for mobile phone traces: current methods, challenges and opportunities
In this work, we present three classes of methods to extract information from triangulated mobile phone signals, and describe applications with different goals in spatiotemporal analysis and urban modeling. Our first challenge is to relate extracted ...
Daily travel behavior: lessons from a week-long survey for the extraction of human mobility motifs related information
Multi-agent models for simulating the mobility behavior of the urban population are gaining momentum due to increasing computing power. Such models pose high demands in terms of input data in order to be reliably able to match real world behavior. To ...
A comparison of Foursquare and Instagram to the study of city dynamics and urban social behavior
Social media systems allow a user connected to the Internet to provide useful data about the context in which they are at any given moment, such as Instagram and Foursquare, which are called participatory sensing systems. Location sharing services are ...
Inferring human activities from GPS tracks
The collection of huge amount of tracking data made possible by the widespread use of GPS devices, enabled the analysis of such data for several applications domains, ranging from traffic management to advertisement and social studies. However, the raw ...
Understanding urban human activity and mobility patterns using large-scale location-based data from online social media
Location-based check-in services enable individuals to share their activity-related choices providing a new source of human activity data for researchers. In this paper urban human mobility and activity patterns are analyzed using location-based data ...
On the importance of temporal dynamics in modeling urban activity
The vast amount of available spatio-temporal data of human activities and mobility has given raise to the rapidly emerging field of urban computing/informatics. Central to the latter is understanding the dynamics of the activities that take place in an ...
Prediction of user location using the radiation model and social check-ins
Location-based social networks serve as a source of data for a wide range of applications, from recommendation of places to visit to modelling of city traffic, and urban planning. One of the basic problems in all these areas is the formulation of a ...
Fast and exact network trajectory similarity computation: a case-study on bicycle corridor planning
Given a set of trajectories on a road network, the goal of the All-Pair Network Trajectory Similarity (APNTS) problem is to calculate the similarity between all trajectories using the Network Hausdorff Distance. This problem is important for a variety ...
Modeling urban traffic dynamics in coexistence with urban data streams
Classic paradigm of scientific modeling is mainly based on a set of previously, accepted or assumed theories about the target phenomena and a validation procedure by limited observations. Therefore, normally data has a supporting role in the modeling ...
Spatiotemporal periodical pattern mining in traffic data
The widespread use of road sensors has generated huge amount of traffic data, which can be mined and put to various different uses. Finding frequent trajectories from the road network of a big city helps in summarizing the way the traffic behaves in the ...
From data to knowledge: city-wide traffic flows analysis and prediction using bing maps
- Anna Izabel J. Tostes,
- Fátima de L. P. Duarte-Figueiredo,
- Renato Assunção,
- Juliana Salles,
- Antonio A. F. Loureiro
Traffic jam is a common contemporary society issue in urban areas. City-wide traffic modeling, visualization, analysis, and prediction are still challenges in this context. Based on Bing Maps information, this work aims to acquire, aggregate, analyze, ...
Finding frequent sub-trajectories with time constraints
With the advent of location-based social media and location-acquisition technologies, trajectory data are becoming more and more ubiquitous in the real world. Trajectory pattern mining has received a lot of attention in recent years. Frequent sub-...
Analyzing the composition of cities using spatial clustering
Cities all around the world are in constant evolution due to numerous factors, such as fast urbanization and new ways of communication and transportation. Since understanding the composition of cities is the key to intelligent urbanization, there is a ...
Real-time air quality monitoring through mobile sensing in metropolitan areas
Traditionally, pollution measurements are performed using expensive equipment at fixed locations or dedicated mobile equipment laboratories. This is a coarse-grained and expensive approach where the pollution measurements are few and far in-between. In ...
Exploring venue-based city-to-city similarity measures
In this work we explore the use of incidentally generated social network data for the folksonomic characterization of cities by the types of amenities located within them. Using data collected about venue categories in various cities, we examine the ...
Whose "city of tomorrow" is it?: on urban computing, utopianism, and ethics
In this article I discuss some ethical and moral ramifications of the future envisioned by urban computing. In doing so, I make analogies to twentieth century utopian visions of the "city of tomorrow," so that we might see the historical context of a ...
Cited By
- Kaminka G and Fridman N (2018). Simulating Urban Pedestrian Crowds of Different Cultures, ACM Transactions on Intelligent Systems and Technology, 9:3, (1-27), Online publication date: 31-May-2018.
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Chattapadhyay S Mathematisation of the Urban and Not Urbanisation of Mathematics: Smart Cities and the Secret of Urban Data, SSRN Electronic Journal, 10.2139/ssrn.2696319
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Popa D, Wijesundara M, Dorsey K, Herr J and Pisano A (2014). Sensor selection for outdoor air quality monitoring SPIE Sensing Technology + Applications, 10.1117/12.2049473, , (91160D), Online publication date: 5-Jun-2014.
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Cullen A, Mazhar M, Smith M, Lithander F, Ó Breasail M and Henderson E (2022). Wearable and Portable GPS Solutions for Monitoring Mobility in Dementia: A Systematic Review, Sensors, 10.3390/s22093336, 22:9, (3336)
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KDD '22: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data MiningUrbanization's rapid progress has led to many big cities, which have modernized many people's lives but also engendered big challenges, such as air pollution, increased energy consumption and traffic congestion. Tackling these challenges were nearly ...