- Paper submission
- June 2, 2013
- Notification of acceptance
- June 22, 2013
- Camera-ready copies due
- June 30, 2013
- Workshop date
- August 11, 2013
- Workshop Summary. UrbComp
2014 will be held in New York City!
Award: A Review of Urban Computing for Mobile Phone
Traces: Current Methods, Challenges and Opportunities.
Shan Jiang, Gaston Fiore, Yingxiang Yang, Joseph Ferreira, Emilio
Frazzoli, Marta González (Plaque)
- Workshop Location: "Superior A" Room in the
- We will have a Panel Discussion on Urban Computing at the end.
- Keynote speech: Computational Urban Sciences: Emerging Opportunities
founding director of the Computation Institute's Urban Center for Computation
Traditionally, urban data has been historical and
course-grained, enabling only general questions of the form "what should have
been done 10, 20, 50 years ago?" New data sources today can enable questions of
the form "what should we do now," provided that appropriate computing and data
analytics capabilities are applied. Data streams published by cities like
Chicago are catalyzing an expanding community of entrepreneurs, academics, and
companies developing new urban applications and services. Through internal data
sharing partnerships between city governments academia, and industry, even more
detailed and comprehensive questions can be asked, ultimately supporting a
transition from purely reactive to proactive policy and planning. Charlie
Catlett will provide an overview of interdisciplinary urban science projects and
opportunities in Chicago that apply computational sciences to understanding
- Submission deadline is extended
to June 2, 2013.
Call For Papers.
- Website launched (Mar. 25, 2013)
Aims and Scope
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.
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.
Some representative projects and literatures
can be found from
This workshop provides the professionals, researchers, and
practitioners who are interested in sensing/mining/understanding
city dynamics with a platform where they can discuss and share the
state-of-the-art of urban computing development and applications,
present their ideas and contributions, and set future directions in
emerging innovative research for urban computing.
A number of selected quality papers will be
invited to a well-known international journal.
Topics of Interest
Topics of interest include, but not limited to, the following aspects :
informatics: acquisition, aggregation, and analysis of big data
City-wide traffic modeling, visualization, analysis, and prediction
City-wide human mobility modeling, visualization, and understanding
Urban computing for urban planning and city configuration evaluation
Urban environment/pollution/energy consumption monitoring and data analysis
City-wide intelligent transportation systems
detection and event discovery in a city
Social behavior modeling, understanding, and patterns mining in urban spaces
Discover regions of
interests and regions of different functions
transportation data, such as ticketing data in bus and subway systems, road
pricing data, and taxi data
City-wide mobile social applications in urban areas
Location-based social networks enabling urban computing scenarios
Smart recommendations in urban spaces
Intelligent delivery services in cities
Mining data from the Internet of
Things in urban areas