Exploiting a fleet of UAVs for monitoring and data acquisition of a distributed sensor network

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 devel...

Full description

Saved in:
Bibliographic Details
Published inNeural computing & applications Vol. 34; no. 7; pp. 5041 - 5054
Main Authors MahmoudZadeh, Somaiyeh, Yazdani, Amirmehdi, Elmi, Atabak, Abbasi, Amin, Ghanooni, Pooria
Format Journal Article
LanguageEnglish
Published London Springer London 01.04.2022
Springer Nature B.V
Subjects
Artificial Intelligence
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Data collection
Data Mining and Knowledge Discovery
Distributed sensor systems
Environmental monitoring
Evolutionary algorithms
Evolutionary computation
Image Processing and Computer Vision
Meteorology
Mission planning
Optimization
Probability and Statistics in Computer Science
Sensors
Special Issue on Computational Intelligence-based Control and Estimation in Mechatronic Systems
Unmanned aerial vehicles
Differential evolution
Mission planning
Multi-UAVs
Sensor network
Online AccessGet full text

Cover

More Information
Summary: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 constrains of the UAV payload and battery capacity. The proposed mission planner system employs the differential evolution optimization algorithm enabling UAVs to maximize the number of visited sensor nodes given the priority of the sensors and avoiding 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.
ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-021-05906-x