Energy-Efficient UAV Networks in 6G-IoT for Sustainable Smart Cities

The integration of Unmanned Aerial Vehicles (UAV) networks into 6G-IoT framework is discussed in this paper using cross geometry optimization for air-to-ground geometry. The proposed model suggests that line of sight-based energy models have dual state path loss and signal-to-interference-plus-noise ratio (SINR) based coverage. Moreover, the energy analysis of both models demonstrates an alternative profile of power components of cruises at ultra-reliable lowlatency communications (URLLC) and coverage limitations. Simulations are performed at 28 GHz frequency and it is observed that five UAVs covering a 1 ~km2 area of 100 metres achieve 100 percent coverage probability with 2.01 milli-seconds end-to-end latency and energy/bit of almost 1 0 0 nano-joule. The integrated model unifies line of sight probability, dual state path loss, SINR, end-to-end latency, propulsion power to guide optimization speed, and deployment density under URLLC and coverage constraints. This approach supports mission design for public safety, infrastructure surveillance, environmental monitoring, and urban mobility, emphasizing edge intelligence, beam management, and cross-layer co-design for reliable, lowlatency, and energy-efficient aerial connectivity.