Best Paper Award

General Introduction

Drones 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 June.

The Prize:

– One research article and one review will be selected;
– Each winner will receive CHF 500, a certificate, and a free voucher for article processing fees that is valid for one year.

Drones Best Paper Award
Winner announcement: 31 May 2025

Eligibility and Requirements

– All papers published in the Drones 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


16 pages, 4096 KiB  
Processing and Interpretation of UAV Magnetic Data: A Workflow Based on Improved Variational Mode Decomposition and Levenberg–Marquardt Algorithm
by Yaoxin Zheng, Shiyan Li, Kang Xing and Xiaojuan Zhang
Drones 2022, 6(1), 11; - 3 Jan 2022
36 pages, 2000 KiB  
A Review of Counter-UAS Technologies for Cooperative Defensive Teams of Drones
by Vittorio Ugo Castrillo, Angelo Manco, Domenico Pascarella and Gabriella Gigante
Drones 2022, 6(3), 65; - 1 Mar 2022

Award Committee

Dr. Diego Gonzalez-Aguilera Chairman
University of Salamanca
Dr. Xiwang Dong
Dr. Eben Broadbent
University of Florida
Prof. Dr. Petros S. Bithas
Digital IndustryTechnologies Department, National and Kapodistrian University of Athens


30 pages, 1632 KiB  
UAV-Enabled Mobile Edge-Computing for IoT Based on AI: A Comprehensive Review
by Yassine Yazid, Imad Ez-Zazi, Antonio Guerrero-González, Ahmed El Oualkadi and Mounir Arioua
Drones 2021, 5(4), 148; - 13 Dec 2021
20 pages, 43356 KiB  
A Citizen Science Unmanned Aerial System Data Acquisition Protocol and Deep Learning Techniques for the Automatic Detection and Mapping of Marine Litter Concentrations in the Coastal Zone
by Apostolos Papakonstantinou, Marios Batsaris, Spyros Spondylidis and Konstantinos Topouzelis
Drones 2021, 5(1), 6; - 18 Jan 2021

Award Committee

Dr. Diego Gonzalez-Aguilera Chairman
University of Salamanca
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