Spatio-Temporal Analysis of Urban Data and its Application for Smart Cities
Abstract
With the advent of smart sensor devices and Internet of Things (IoT) in the rapid urbanizing
cities, data is being generated, collected and analyzed to solve urban problems in the areas
of transportation, epidemiology, emergency management, economics, and sustainability etc.
The work in this area basically involves analyzing one or more types of data to identify
and characterize their impact on other urban phenomena like traffic speed and ride-sharing,
spread of diseases, emergency evacuation, share market and electricity demand etc. In this
work, we perform spatio-temporal analysis of various urban datasets collected from different
urban application areas. We start with presenting a framework for predicting traffic demand
around a location of interest and explain how it can be used to analyze other urban activities.
We use a similar method to characterize and analyze spatio-temporal criminal activity in
an urban city. At the end, we analyze the impact of nearby traffic volume on the electric
vehicle charging demand at a charging station.
Collections
- Masters Theses [19662]