Romanian Journal of Information Science and Technology (ROMJIST)

An open – access publication

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ROMJIST is a publication of Romanian Academy,
Section for Information Science and Technology

Editor – in – Chief:
Radu-Emil Precup

Honorary Co-Editors-in-Chief:
Horia-Nicolai Teodorescu
Gheorghe Stefan

Secretariate (office):
Adriana Apostol
Adress for correspondence: romjist@nano-link.net (after 1st of January, 2019)

Founding Editor-in-Chief
(until 10th of February, 2021):
Dan Dascalu

Editing of the printed version: Mihaela Marian (Publishing House of the Romanian Academy, Bucharest)

Technical editor
of the on-line version:
Lucian Milea (University POLITEHNICA of Bucharest)

Sponsor:
• National Institute for R & D
in Microtechnologies
(IMT Bucharest), www.imt.ro

ROMJIST Volume 23, No. S, 2020, pp. S53-S66
 

Dan-Marius DOBREA, Monica-Claudia DOBREA
An autonomous UAV system for video monitoring of the quarantine zones

ABSTRACT: In this paper, a comparative study between two classification approaches was done, namely, between a Support Vector Machine (SVM) neural network - as a classical machine learning approach -, and four different deep learning classification systems, considered today to be the state-of-the-art systems in computer vision. Two embedded companion computers, a Raspberry Pi and a Jetson Nano, placed on a HoverGames quadcopter support the classification systems that were developed and deployed to identify humans. The ultimate goal of this research consists in developing a quadcopter system endowed with the capabilities of following a pre-programmed flight route and simultaneously detecting humans as well as of warning the system operator to reinforce the quarantine zones. The obtained results demonstrated the superior performances provided by the deep learning approach: more than six times faster than the classical approach, and with a correct classification performance higher than 90% on a direct stream of video data.

KEYWORDS: UAV, HoverGames, PX4, QGroundControl, deep learning, HOG, SVM

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