Prezioso, Edoardo (2024) Artificial Intelligence methodologies for Smart Mobility. [Tesi di dottorato]
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| Tipologia del documento: | Tesi di dottorato |
|---|---|
| Lingua: | English |
| Titolo: | Artificial Intelligence methodologies for Smart Mobility |
| Autori: | Autore Email Prezioso, Edoardo edoardo.prezioso@unina.it |
| Data: | 11 Marzo 2024 |
| Istituzione: | Università degli Studi di Napoli Federico II |
| Dipartimento: | Matematica e Applicazioni "Renato Caccioppoli" |
| Dottorato: | Matematica e Applicazioni |
| Ciclo di dottorato: | 36 |
| Coordinatore del Corso di dottorato: | nome email Moscariello, Gioconda gioconda.moscariello@unina.it |
| Tutor: | nome email Festa, Paola [non definito] |
| Data: | 11 Marzo 2024 |
| Parole chiave: | Artificial Intelligence, Deep Learning, Smart Mobility |
| Settori scientifico-disciplinari del MIUR: | Area 01 - Scienze matematiche e informatiche > INF/01 - Informatica |
| Depositato il: | 15 Mar 2024 15:49 |
| Ultima modifica: | 16 Mar 2026 11:33 |
| URI: | http://www.fedoa.unina.it/id/eprint/15458 |
Abstract
Nowadays, the rapid pace of urbanization presents unprecedented opportunities and challenges, catalyzing the adoption of innovative technologies for data-driven decision-making in urban contexts. Central to this transformation is the Smart City paradigm, underpinned by Deep Learning frameworks, a vital subset of Artificial Intelligence. These frameworks, evolving from rudimentary biological models to advanced neural networks, significantly enhance urban life by bolstering safety, efficiency, and sustainability. This work introduces the SMart Analytics in Roads and Transportations (SM.A.R.T) framework, a novel approach employing state-of-the-art forecasting methodology named ENCODE and cutting-edge computer vision techniques for real-time detection and tracking in urban traffic and crowd management. It highlights the pivotal role of neural networks in advancing urban computational research and shaping the future of Smart City initiatives, emphasizing the critical need for ongoing innovation in AI applications.
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