Aseel Khalid Ahmed

Background: Failures of communication usually occur during natural disasters, therefore signaling the importance of flexible networks. Unmanned Aerial Vehicles (UAVs) are anticipated to solve this problem by acting as on-the-move networks in the disaster-stricken regions. However, barriers that include challenges in UAV control coordination, resources allocation as well as security of the data being drawn are still pushing the technology backward. Objective: The article seeks to design and analyze enhanced heuristics for employing UAVs in disaster communications to enhance performance, availability, and security. Methods: Both primary, semi-structured interview and survey and post-disaster reports as well as secondary, computational analysis based on MATLAB and NS - 3 simulations were used as the data collection technique. Five algorithms: Multi-UAV Coordination, Dynamic Resource Allocation with Security, Hybrid Communication Framework, AI-Driven Path Optimization, Privacy-Preserving Data Sharing were implemented and incorporated. Theoretical models built on the basis of multi- objective optimization and the theory of games confirmed work ability to scale. Results: The introduced algorithms increased coverage by 75%, decreased latency by 27 percent, and also introduced 30 percent energy efficiency. Average privacy compliance levels floated above 90%, and an advanced resource allocation model achieved equal distribution. All these enhancements were affirmed in urban, rural and mountainous regions further proving versatility and stability. Conclusion: The article proposes a framework for UAV-enabled disaster communication system that can incorporate advanced algorithm and theoretical models to overcome the coordination challenge while ensuring the efficiency and security of the system. The presented results can be considered to be the reliable base for the UAVs usage in disaster situations.

: Background: Unmanned aerial vehicle (UAV) networks as an important part of the modern telecommunication are gaining importance in various situations, including rural coverage, urban settings and emergency situations. However, Interference, scalability and energy efficiency still pose problems to the advancement of wireless networks. Objective: The aim of current study is to integrate and assess an adaptive frequency management technique for improving the performance of communication networks involving UAVs in terms of interference, transmission rates, and reliability within different deployment settings. Methods: Experimental and simulated studies were performed to evaluate the effectiveness of the algorithm in this combination. Performance measurements in terms of latency, throughput, packet loss, energy consumption and signal strength were made under rural, urban and emergency conditions. The adaptable algorithm used certain working frequencies depending on the interferences present and the network performance parameters recorded. Results: The algorithm showed very distinct enhancements in all models and positions, decreasing latency by 20.5%, enhancing throughput by 14.5%, and decreasing the packet loss by 57.6% in the urban site settings. Other executed experiments documented improved energy efficiency and communication reliability in rural and emergency situations. Conclusion: The adaptive frequency management algorithm proposed by the authors effectively solves significant issues of critical concern in UAV networks while offering robust scalability for next-generation telecommunications infrastructure. The future research recommendation incorporates the combination of the proposed optimization with other complementary approaches and/or the testing of the developed system at more severe actual conditions.