In the aftermath of natural or man-made disasters, where traditional communication infrastructures are damaged or disrupted, re-establishing emergency wireless communication networks is crucial to restore connectivity in affected areas for first response and rescue operations. In order to handle these emergency scenarios, establishing an effective rescue and recovery system is essential. After a disaster, Unmanned Aerial Vehicles (UAVs) can be used as a temporary aerial base station in support to fifth-generation (5G) networks to extend the coverage in the disaster area. However, ensuring reliable connectivity and improving coverage are essential to maintain continuous communication. The main objective considered in this paper is to maximize the number of user equipment (UE) covered with an optimal number of UAV deployments, characterizing the air-to-ground (A2G) channel, and identifying the optimal locations for this Unmanned Base Station (UBS) deployment that ensures continuity of communication service to the disaster area. This paper proposes a K-means Clustering with Gray Wolf Optimization (KCGWO) algorithm for UAV placement integrated with Device-to-Device (D2D) communication to provide connectivity and enhance coverage in a disaster area. We investigate our proposed model’s performance in terms of delay, coverage probability, and system capacity. Simulations result shows that our proposed KCGWO model performs better in comparison with existing methods such as Particle Swarm Optimization (PSO) and K-means, highlighting their suitability for providing efficient and reliable disaster-resilient communication in areas that are outside the network coverage.