Best Paper Award

The Smart Cities Best Paper Award is granted annually to highlight publications of high quality, scientific significance, and extensive influence. The evaluation committee members choose two articles of exceptional quality that were published in the journal the year before the previous year and announce them online by the end of April.

The Prize:
– 1 research article and 1 review will be selected.
– Each winner will receive CHF 500, a certificate, and a free voucher for article processing fees valid for one year.

Award FAQ

 
Smart Cities Best Paper Award
 

Eligibility and Requirements

– All papers published in the Smart Cities will be eligible (Both regular and Special Issue submissions).

Selection Criteria

– Scientific merit and broad impact;
– Originality of the research objectives and/or the ideas presented;
– Creativity of the study design or uniqueness of the approaches and concepts;
– Clarity of presentation;
– Citations and downloads.
 
Past Winners
 
Year: 

Winner

22 pages, 1960 KB  
Review
Digital Twin Technology in Built Environment: A Review of Applications, Capabilities and Challenges
by Yalda Mousavi, Zahra Gharineiat, Armin Agha Karimi, Kevin McDougall, Adriana Rossi and Sara Gonizzi Barsanti
Smart Cities 2024, 7(5), 2594-2615; https://doi.org/10.3390/smartcities7050101 - 10 Sep 2024
26 pages, 2755 KB  
Article
A Retrieval-Augmented Generation Approach for Data-Driven Energy Infrastructure Digital Twins
by Saverio Ieva, Davide Loconte, Giuseppe Loseto, Michele Ruta, Floriano Scioscia, Davide Marche and Marianna Notarnicola
Smart Cities 2024, 7(6), 3095-3120; https://doi.org/10.3390/smartcities7060121 - 24 Oct 2024

Winner

23 pages, 5372 KB  
Article
A Comparative Analysis of Multi-Label Deep Learning Classifiers for Real-Time Vehicle Detection to Support Intelligent Transportation Systems
by Danesh Shokri, Christian Larouche and Saeid Homayouni
Smart Cities 2023, 6(5), 2982-3004; https://doi.org/10.3390/smartcities6050134 - 23 Oct 2023
34 pages, 1314 KB  
Review
Multivariate Time-Series Forecasting: A Review of Deep Learning Methods in Internet of Things Applications to Smart Cities
by Vasilis Papastefanopoulos, Pantelis Linardatos, Theodor Panagiotakopoulos and Sotiris Kotsiantis
Smart Cities 2023, 6(5), 2519-2552; https://doi.org/10.3390/smartcities6050114 - 23 Sep 2023
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