Exploiting a Fleet of UAVs for Monitoring and Data Acquisition of a Distributed Sensor Network

TL;DR

This paper introduces a UAV fleet-based system for efficient data collection from large distributed sensor networks, optimizing mission planning with Differential Evolution to maximize sensor visits while respecting UAV constraints.

Contribution

It presents a novel collaborative mission planning system using Differential Evolution for UAVs to efficiently monitor and collect data from sensor networks.

Findings

The proposed planner maximizes sensor visits considering priorities.

Simulation confirms the system's effectiveness and fidelity.

The approach reduces redundant data collection.

Abstract

This study proposes an efficient data collection strategy exploiting a team of Unmanned Aerial Vehicles (UAVs) to monitor and collect the data of a large distributed sensor network usually used for environmental monitoring, meteorology, agriculture, and renewable energy applications. The study develops a collaborative mission planning system that enables a team of UAVs to conduct and complete the mission of sensors' data collection collaboratively while considering existing constraints of the UAV payload and battery capacity. The proposed mission planner system employs the Differential Evolution (DE) optimization algorithm enabling UAVs to maximize the number of visited sensor nodes given the priority of the sensors and avoiding the redundant collection of sensors' data. The proposed mission planner is evaluated through extensive simulation and comparative analysis. The simulation results confirm the effectiveness and fidelity of the proposed mission planner to be used for the distributed sensor network monitoring and data collection.