A Resting Drone-Enabled Surveillance Framework for Real-Time Monitoring With Resource Efficiency in IoT-Based Smart City
Hyeongjin Kim, Hyunbum Kim, Mohsen Guizani
Abstract
Drones or UAVs (Unmanned Aerial Vehicles) are increasingly utilized with IoT (Internet of Things) to enhance security surveillance and environmental monitoring within smart cities. Although path planning algorithms, deployment strategies, and charging station optimization techniques have been explored to improve operational efficiency, the physical limitations of battery capacity remain a significant challenge. This study introduces the concept of a "resting drone," a specialized drone capable of attaching to structures or walls through structural modifications. By doing so, it can perform environmental monitoring and surveillance tasks without operating its motors, thus conserving energy. Furthermore, we conducted simulations based on real hardware data of resting drones to analyze their operations, including resting, movement, target area monitoring, and resource charging, within a smart city environment. A new movement algorithm was proposed to enhance the resource efficiency of the resting drones. The study compares the resource efficiency of resting drones with that of conventional drones. The results show that environmental monitoring coverage increases significantly, from 60% to 315%, depending on the movement algorithm used.