This article investigates the effectiveness of utilizing reconfigurable intelligent surface (RIS) into a system that employs non-orthogonal multiple access (NOMA)-aided mobile-edge computing (MEC) incorporating unmanned aerial vehicle (UAV) within Internet of Things (IoT) networks. The proposed system introduces a synergistic framework, where the RIS’s channel enhancement capabilities and the UAV’s dynamic positioning are jointly exploited to maximize the utilization of low-latency computation resources from proximate MEC severs. Accordingly, a crucial criterion for assessing the system effectiveness is its ability to provide sustainable communication and computational services for resource-constrained devices. Additionally, to assess the computation offloading efficiency of the system, the derivation of a closed-form formulation termed successful computation probability (SCP) is leveraged under fading channels of Nakagami-m. Eventually, the precision of the system model is validated through extensive numerical simulations, demonstrating that increasingly deploying RIS elements can achieve greater computation offloading reliability while requiring less transmission power, hence highlighting significant energy savings.