An Optimized Technique for Securing Modern Smart Cities Using Equipped Crowed-Sensing Unmanned aerial vehicles | ||
| International Journal of Telecommunications | ||
| Volume 05, Issue 02, July 2025, Pages 1-15 PDF (2.37 M) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/ijt.2025.392623.1117 | ||
| Authors | ||
| Amr Aboghanem* 1; Hanan Amer2; Abeer Khalil3 | ||
| 1dep. of Electronics and Electrical Communications Engineering, Air Defense Collage, Egyptian Military Academy, Cairo, Egypt, | ||
| 2Electronics and Communications Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt | ||
| 3Electronics and communications department Faculty of Engineering, Mansoura University, Egypt | ||
| Abstract | ||
| Unmanned aerial vehicles (UAVs) have become a vital and indispensable tool in modern disaster management, especially in smart cities that rely on complex infrastructure and communication networks. This paper addresses the pivotal importance of UAVs in disaster prevention efforts, with a particular focus on the challenges posed by GNSS signal disturbances, which hinder accurate navigation and relief efforts. In this paper, we present an efficient and robust system that aims to establish a secure and reliable communication channel between UAVs—equipped with crowd-sensing techniques and advanced estimation filters such as Extended Kalman Filters and Particle Filters—and the ground control station. This system ensures continuous communication even in the absence of GNSS signals, enabling UAVs to efficiently perform their vital tasks. Furthermore, we propose a secure communication method based on robust cryptographic steganography, combining the Advanced Encryption Standard (AES) and stego-images using discrete wavelet (DWT) coefficients. The test results confirm the effectiveness of the proposed method, as its performance was successfully evaluated using the mean square error (MSE), maximum signal-to-noise ratio (PSNR), and correlation (COR) metrics. | ||
| Keywords | ||
| Unmanned Aerial Vehicle (UAV); Global Navigation Satellite System (GNSS); Inertial Measurement Unit (IMU); Extended Kalman Filter (EKF); Particle Filter (PF) | ||
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