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FANET Experiment: Real-Time Surveillance Applications Connected to Image Processing System

Author: Bashir Olaniyi Sadiq; Muhammed Yusuf Abiodun; Sikiru Olayinka Zakariyya
Publisher: preprint
Published: 2022
Section: School of Engineering and Applied Sciences

Abstract

The major goal of this paper is to use image enhancement techniques for enhancing and
extracting data in FANET applications to improve the efficiency of surveillance. The proposed
conceptual system design can improve the likelihood of FANET operations in oil pipeline
surveillance, and sports and media coverage with the ultimate goal of providing efficient services to
those who are interested. The system architecture model is based on current scientific principles and
developing technologies. A FANET, which is capable of gathering image data from video-enabled
drones, and an image processing system that permits data collection and analysis are the two primary
components of the system. Based on the image processing technique, a proof of concept for efficient
data extraction and enhancement in FANET situations and possible services is illustrated.