ArticleFrontiers in big data2023
Big data analytics and smart cities: applications, challenges, and opportunities.
Article in Frontiers in big data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Mobile application traffic reveals multifunctional use patterns in Parisian parks.Scientific reports · 2026Article
- An Integrated IoT-Based Multi-Sensor Framework for Real-Time Indoor Environment and Safety Monitoring.Sensors (Basel, Switzerland) · 2026Article
- Real-time AI-driven trend analytics for smart city digital services using streaming data.Frontiers in big data · 2026Article
- The Impact of Scale on Extracting Individual Mobility Patterns from Location-Based Social Media.Sensors (Basel, Switzerland) · 2024Article
- Enhancing Urban Data Analysis: Leveraging Graph-Based Convolutional Neural Networks for a Visual Semantic Decision Support System.Sensors (Basel, Switzerland) · 2024Article
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Authors and funding
1 author.
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Abstract
Urban environments continuously generate larger and larger volumes of data, whose analysis can provide descriptive and predictive models as valuable support to inspire and develop data-driven Smart City applications. To this aim, Big data analysis and machine learning algorithms can play a fundamental role to bring improvements in city policies and urban issues. This paper introduces how Big Data analysis can be exploited to design and develop data-driven smart city services, and provides an overview on the most important Smart City applications, grouped in several categories. 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 an approach for spatio-temporal crime forecasting (tested on Chicago crime data), the second one is methodology to discover mobility hotsposts and trajectory patterns from GPS data (tested on Beijing taxi traces), the third one is an approach to discover predictive epidemic patterns from mobility and infection data (tested on real COVID-19 data). The presented real-world cases prove that data analytics models can effectively support city managers in tackling smart city challenges and improving urban applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.