E3-HetAIoT: A Novel Energy-Efficient Air–Ground Integrated HetAIoT for Emergency Rescue

Abstract

In recent years, with the acceleration process of smart cities, the Artificial Intelligence of Things (AIoT) has become a novel approach for emergency rescue. However, due to small capacity and heterogeneity, AIoT nodes are facing various energy limitations and complex routing challenges. Therefore, emergency AIoT often have issues, such as data transmission failures, energy consumption, reduced network lifespan, and latency. To overcome these problems, this study proposes an energy efficiency emergency air–ground integrated heterogeneous AIoT (E3-HetAIoT) structure to improve the energy management efficiency of smart cities. First, we adopt a cell-based clustering mechanism, and the multiobjective zebra optimization algorithm (M-ZOA) is used to select cluster heads (CHs) and super nodes (UNs). The UN uses an urgency level-driven energy efficient sleep scheduling (U-ESS) mechanism to balance the remaining energy of sensors, especially in scheduling sleep time slots for sensors have energy below typical threshold. Second, an air–ground integrated data transmission mechanism is adopted, in which the generator de bits pseudo aleatorios (GBPA) is used to eliminate redundant data in CH and improve security. Then, the data packets are divided into normal packets and emergency ones. The normal packets wait for transmission of unmanned aerial vehicle (UAV) UAVs as intelligent mobile agents (U-iAgents), the trajectory of U-iAgents are dynamically predicted by dueling double deep Q-Network (Dueling-DDQN), meanwhile emergency data packets are immediately transmitted through inter cluster routing. Simulation results demonstrate that compared to existing algorithms, our proposed E3-HetAIoT framework achieves lower energy consumption and higher network lifetime, respectively.