ABSTRACT Unmanned aerial vehicles (UAVs) play a pivotal role in disaster response by enabling rapid information gathering from widely distributed sensor nodes. In resource‐constrained scenarios, limitations in the number of UAVs and their onboard energy pose significant challenges in swiftly collecting and analysing high‐priority data. In this paper, we tackle the crucial challenge of efficient multi‐UAV‐aided data collection in resource‐constrained Internet of Things (IoT) environments where UAVs function as mobile data collectors. Given the inherent heterogeneity in data value and spatial distribution of IoT devices, a sophisticated approach is necessary to maximise data collection value while optimising energy consumption and coverage. This paper introduces a novel UAV‐assisted IoT data collection model tailored for resource‐constrained environments. By constructing a virtual backbone network and employing the NSGA‐II algorithm for multi‐objective optimisation, our model effectively routes data and schedules UAVs to maximise both data value and coverage. Extensive simulations demonstrate that our proposed algorithm achieves a superior balance between value and quantity in resource‐constrained scenarios compared to existing data collection schemes.
An et al. (Thu,) studied this question.