In both disastrous and non-critical situations, the significance of emergency networks cannot be overstated, particularly in the deployment of 6G low-latency networks. Hence, this study explores the transformative potential of irregular reconfigurable intelligent surfaces (IRIS)-aided unmanned aerial vehicle (UAV) systems in revolutionizing emergency networks by offering unparalleled mobility, scalability, resilience, accessibility, and active beamforming capabilities, significantly outperforming traditional systems. In our system model with inbuilt composite path loss and fading-shadowing, a tabu search-based sparse deployment and neighbor extraction-based cross-entropy method for the beamforming optimization of the proposed IRIS-aided UAV are considered. Simulation results revealed that maintaining lower UAV altitudes provide significant weighted sum-rate (WSR) improvement. Additionally, optimizing environmental factors such as shadowing and fading in low-obstructive environments markedly improved the WSR. Furthermore, increasing the size of the RIS exponentially enhanced the WSR performance. In addition, the simulation results demonstrated that IRIS-aided UAV topology surpasses traditional RIS-aided systems by leveraging enhanced spatial diversity and less computations for superior low latency network performance. These findings collectively advocate for a multifaceted optimization strategy encompassing UAV height, environmental conditions, and RIS dimensions. This paper paves the way for the development of more energy-efficient and high-performing communication systems.