An authoritative treatment of urban computing, offering an overview of
the field, fundamental techniques, advanced models, and novel
applications.
Urban computing brings powerful computational techniques to bear on such
urban challenges as pollution, energy consumption, and traffic
congestion. Using today's large-scale computing infrastructure and data
gathered from sensing technologies, urban computing combines computer
science with urban planning, transportation, environmental science,
sociology, and other areas of urban studies, tackling specific problems
with concrete methodologies in a data-centric computing framework. This
authoritative treatment of urban computing offers an overview of the
field, fundamental techniques, advanced models, and novel applications.
Each chapter acts as a tutorial that introduces readers to an important
aspect of urban computing, with references to relevant research. The
book outlines key concepts, sources of data, and typical applications;
describes four paradigms of urban sensing in sensor-centric and
human-centric categories; introduces data management for spatial and
spatio-temporal data, from basic indexing and retrieval algorithms to
cloud computing platforms; and covers beginning and advanced topics in
mining knowledge from urban big data, beginning with fundamental data
mining algorithms and progressing to advanced machine learning
techniques. Urban Computing provides students, researchers, and
application developers with an essential handbook to an evolving
interdisciplinary field.
