Cargando…

A Collaborative UAV-WSN Network for Monitoring Large Areas

Large-scale monitoring systems have seen rapid development in recent years. Wireless sensor networks (WSN), composed of thousands of sensing, computing and communication nodes, form the backbone of such systems. Integration with unmanned aerial vehicles (UAVs) leads to increased monitoring area and...

Descripción completa

Detalles Bibliográficos
Autores principales: Popescu, Dan, Dragana, Cristian, Stoican, Florin, Ichim, Loretta, Stamatescu, Grigore
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308614/
https://www.ncbi.nlm.nih.gov/pubmed/30513655
http://dx.doi.org/10.3390/s18124202
_version_ 1783383230417731584
author Popescu, Dan
Dragana, Cristian
Stoican, Florin
Ichim, Loretta
Stamatescu, Grigore
author_facet Popescu, Dan
Dragana, Cristian
Stoican, Florin
Ichim, Loretta
Stamatescu, Grigore
author_sort Popescu, Dan
collection PubMed
description Large-scale monitoring systems have seen rapid development in recent years. Wireless sensor networks (WSN), composed of thousands of sensing, computing and communication nodes, form the backbone of such systems. Integration with unmanned aerial vehicles (UAVs) leads to increased monitoring area and to better overall performance. This paper presents a hybrid UAV-WSN network which is self-configured to improve the acquisition of environmental data across large areas. A prime objective and novelty of the heterogeneous multi-agent scheme proposed here is the optimal generation of reference trajectories, parameterized after inter- and intra-line distances. The main contribution is the trajectory design, optimized to avoid interdicted regions, to pass near predefined way-points, with guaranteed communication time, and to minimize total path length. Mixed-integer description is employed into the associated constrained optimization problem. The second novelty is the sensor localization and clustering method for optimal ground coverage taking into account the communication information between UAV and a subset of ground sensors (i.e., the cluster heads). Results show improvements in both network and data collection efficiency metrics by implementing the proposed algorithms. These are initially evaluated by means of simulation and then validated on a realistic WSN-UAV test-bed, thus bringing significant practical value.
format Online
Article
Text
id pubmed-6308614
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-63086142019-01-04 A Collaborative UAV-WSN Network for Monitoring Large Areas Popescu, Dan Dragana, Cristian Stoican, Florin Ichim, Loretta Stamatescu, Grigore Sensors (Basel) Article Large-scale monitoring systems have seen rapid development in recent years. Wireless sensor networks (WSN), composed of thousands of sensing, computing and communication nodes, form the backbone of such systems. Integration with unmanned aerial vehicles (UAVs) leads to increased monitoring area and to better overall performance. This paper presents a hybrid UAV-WSN network which is self-configured to improve the acquisition of environmental data across large areas. A prime objective and novelty of the heterogeneous multi-agent scheme proposed here is the optimal generation of reference trajectories, parameterized after inter- and intra-line distances. The main contribution is the trajectory design, optimized to avoid interdicted regions, to pass near predefined way-points, with guaranteed communication time, and to minimize total path length. Mixed-integer description is employed into the associated constrained optimization problem. The second novelty is the sensor localization and clustering method for optimal ground coverage taking into account the communication information between UAV and a subset of ground sensors (i.e., the cluster heads). Results show improvements in both network and data collection efficiency metrics by implementing the proposed algorithms. These are initially evaluated by means of simulation and then validated on a realistic WSN-UAV test-bed, thus bringing significant practical value. MDPI 2018-11-30 /pmc/articles/PMC6308614/ /pubmed/30513655 http://dx.doi.org/10.3390/s18124202 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Popescu, Dan
Dragana, Cristian
Stoican, Florin
Ichim, Loretta
Stamatescu, Grigore
A Collaborative UAV-WSN Network for Monitoring Large Areas
title A Collaborative UAV-WSN Network for Monitoring Large Areas
title_full A Collaborative UAV-WSN Network for Monitoring Large Areas
title_fullStr A Collaborative UAV-WSN Network for Monitoring Large Areas
title_full_unstemmed A Collaborative UAV-WSN Network for Monitoring Large Areas
title_short A Collaborative UAV-WSN Network for Monitoring Large Areas
title_sort collaborative uav-wsn network for monitoring large areas
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308614/
https://www.ncbi.nlm.nih.gov/pubmed/30513655
http://dx.doi.org/10.3390/s18124202
work_keys_str_mv AT popescudan acollaborativeuavwsnnetworkformonitoringlargeareas
AT draganacristian acollaborativeuavwsnnetworkformonitoringlargeareas
AT stoicanflorin acollaborativeuavwsnnetworkformonitoringlargeareas
AT ichimloretta acollaborativeuavwsnnetworkformonitoringlargeareas
AT stamatescugrigore acollaborativeuavwsnnetworkformonitoringlargeareas
AT popescudan collaborativeuavwsnnetworkformonitoringlargeareas
AT draganacristian collaborativeuavwsnnetworkformonitoringlargeareas
AT stoicanflorin collaborativeuavwsnnetworkformonitoringlargeareas
AT ichimloretta collaborativeuavwsnnetworkformonitoringlargeareas
AT stamatescugrigore collaborativeuavwsnnetworkformonitoringlargeareas