Big Data Analytics and Smart Cities: Applications, Challenges and Opportunities
Speaker: Eugenio Cesario – Rende (CS), ItalyTopic(s): Artificial Intelligence, Machine Learning, Computer Vision, Natural language processing
Abstract
The steadily increasing urbanization is causing significant economic and social transformations in urban areas, posing several challenges and raising new issues in city development, public policy, and resource management. However, leveraged by a pervasive and large-scale diffusion of sensing networks in modern cities, huge volumes of geo-referenced urban data are collected every day. Such ever-increasing volumes of urban-related data offer the opportunity to apply data analytics methodologies to discover useful descriptive and predictive models, which can support city managers in tackling the major issues that cities face, including urban mobility, air pollution, virus diffusion, traffic flows, crime forecasts, etc.
This talk introduces how data analysis and machine learning techniques can be exploited to design and develop data-driven models as valuable support to inspire and implement smart city applications and services. Then, it presents three real-case studies showing how data analysis methodologies can provide innovative solutions to deal with smart city issues. The first one is a methodology based on spatial analysis and auto-regressive models for spatio-temporal crime forecasting, which has been tested on crime events occurred in Chicago. The second one is a methodology to discover mobility hotsposts and trajectory patterns from GPS data, which has been tested on Beijing taxi traces. The third one is an approach to discover spatio-temporal predictive epidemic patterns from mobility and infection data, whose experimental evaluation has been carried out on real-world Covid-19 data. The presented real-world cases are aimed to show how data analytics models can provide valuable support for city managers in tackling smart city challenges, to improve urban applications and citizens’ lives.
About this Lecture
Number of Slides: 60Duration: 60 minutes
Languages Available: English, Italian
Last Updated:
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