An Energy Efficient UAV Path Planning for Data Collection in Multi-Node IoT System

Unmanned aerial vehicles (UAVs) have become indispensable instruments in various applications, including surveillance, environmental monitoring, and data collection in Internet-of-Things (IoT) applications. The effectiveness and efficiency of UAV missions are inextricably linked to the path-planning strategies employed. With the modern approach to minimization, the requirement to minimize UAV energy consumption and boost battery time available is growing rapidly. With this objective, this paper presents Energy Constrained-Adaptive Path Construction (EC-APC), as an improved optimization technique for UAV path planning keeping in consideration the battery limits of the UAV. The proposed algorithm, named MNES, uses EC-APC to generate several paths for the UAV to satisfy its energy constraints. Simulation results and complexity analyses corroborate the time complexity advantage and energy-efficient path planning of the proposals.