Paolo Nesi

University of Florence

Italy

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Articles (21)

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2024

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2022

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2022

Collaborators (5)

Luciano Alessandro Ipsaro Palesi

University of Florence

ITALY

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ALA ARMAN

Assistant Professor (RTDa)

ITALY

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Ascanio Rosi

University of Florence

ITALY

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Gianni Pantaleo

University of Florence

ITALY

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Marco Fanfani

Assistant Professor

University of Florence

ITALY

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Paolo Nesi

Research Interests

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Articles (21)

High Precision Traffic Flow Reconstruction via Hybrid Method

Microservices’ libraries enabling server-side business logic visual programming for digital twins

A Unified Knowledge Model for Managing Smart City/IoT Platform Entities for Multitenant Scenarios

Snap4City dashboard manager: A tool for creating and distributing complex and interactive dashboards with no or low coding

Smart City Scenario Editor for General What-If Analysis

Data Sources and Models for Integrated Mobility and Transport Solutions

Explainable Artificial Intelligence for Agile Mediation Propensity Assessment

High Precision Traffic Flow Reconstruction via Hybrid Method

Smart City Digital Twin Framework for Real-Time Multi-Data Integration and Wide Public Distribution

Managing complexity of data models and performance in broker-based Internet/Web of Things architectures

Flexible thermal camera solution for Smart city people detection and counting

Multi Clustering Recommendation System for Fashion Retail

Predicting free parking slots via deep learning in short-mid terms explaining temporal impact of features

Evidence-based clinical engineering: Health information technology adverse events identification and classification with natural language processing

Implementing integrated digital twin modelling and representation into the Snap4City platform for smart city solutions

Predicting and Understanding Landslide Events With Explainable AI

Analyzing Demand with Respect to Offer of Mobility

Estimating CO2 Emissions from IoT Traffic Flow Sensors and Reconstruction

IoT-Enabled Smart Cities: A Review of Concepts, Frameworks and Key Technologies

Classification of users’ transportation modalities from mobiles in real operating conditions

Short-Term Prediction of City Traffic Flow via Convolutional Deep Learning

Collaborators (5)

Luciano Alessandro Ipsaro Palesi

ALA ARMAN

Ascanio Rosi

Gianni Pantaleo

Marco Fanfani

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