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Node Deployment with k-Connectivity in Sensor Networks for Crop Information Full Coverage Monitoring
Wireless sensor networks (WSNs) are suitable for the continuous monitoring of crop information in large-scale farmland. The information obtained is great for regulation of crop growth and achieving high yields in precision agriculture (PA). In order to realize full coverage and k-connectivity WSN de...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5191076/ https://www.ncbi.nlm.nih.gov/pubmed/27941704 http://dx.doi.org/10.3390/s16122096 |
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author | Liu, Naisen Cao, Weixing Zhu, Yan Zhang, Jingchao Pang, Fangrong Ni, Jun |
author_facet | Liu, Naisen Cao, Weixing Zhu, Yan Zhang, Jingchao Pang, Fangrong Ni, Jun |
author_sort | Liu, Naisen |
collection | PubMed |
description | Wireless sensor networks (WSNs) are suitable for the continuous monitoring of crop information in large-scale farmland. The information obtained is great for regulation of crop growth and achieving high yields in precision agriculture (PA). In order to realize full coverage and k-connectivity WSN deployment for monitoring crop growth information of farmland on a large scale and to ensure the accuracy of the monitored data, a new WSN deployment method using a genetic algorithm (GA) is here proposed. The fitness function of GA was constructed based on the following WSN deployment criteria: (1) nodes must be located in the corresponding plots; (2) WSN must have k-connectivity; (3) WSN must have no communication silos; (4) the minimum distance between node and plot boundary must be greater than a specific value to prevent each node from being affected by the farmland edge effect. The deployment experiments were performed on natural farmland and on irregular farmland divided based on spatial differences of soil nutrients. Results showed that both WSNs gave full coverage, there were no communication silos, and the minimum connectivity of nodes was equal to k. The deployment was tested for different values of k and transmission distance (d) to the node. The results showed that, when d was set to 200 m, as k increased from 2 to 4 the minimum connectivity of nodes increases and is equal to k. When k was set to 2, the average connectivity of all nodes increased in a linear manner with the increase of d from 140 m to 250 m, and the minimum connectivity does not change. |
format | Online Article Text |
id | pubmed-5191076 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-51910762017-01-03 Node Deployment with k-Connectivity in Sensor Networks for Crop Information Full Coverage Monitoring Liu, Naisen Cao, Weixing Zhu, Yan Zhang, Jingchao Pang, Fangrong Ni, Jun Sensors (Basel) Article Wireless sensor networks (WSNs) are suitable for the continuous monitoring of crop information in large-scale farmland. The information obtained is great for regulation of crop growth and achieving high yields in precision agriculture (PA). In order to realize full coverage and k-connectivity WSN deployment for monitoring crop growth information of farmland on a large scale and to ensure the accuracy of the monitored data, a new WSN deployment method using a genetic algorithm (GA) is here proposed. The fitness function of GA was constructed based on the following WSN deployment criteria: (1) nodes must be located in the corresponding plots; (2) WSN must have k-connectivity; (3) WSN must have no communication silos; (4) the minimum distance between node and plot boundary must be greater than a specific value to prevent each node from being affected by the farmland edge effect. The deployment experiments were performed on natural farmland and on irregular farmland divided based on spatial differences of soil nutrients. Results showed that both WSNs gave full coverage, there were no communication silos, and the minimum connectivity of nodes was equal to k. The deployment was tested for different values of k and transmission distance (d) to the node. The results showed that, when d was set to 200 m, as k increased from 2 to 4 the minimum connectivity of nodes increases and is equal to k. When k was set to 2, the average connectivity of all nodes increased in a linear manner with the increase of d from 140 m to 250 m, and the minimum connectivity does not change. MDPI 2016-12-09 /pmc/articles/PMC5191076/ /pubmed/27941704 http://dx.doi.org/10.3390/s16122096 Text en © 2016 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 Liu, Naisen Cao, Weixing Zhu, Yan Zhang, Jingchao Pang, Fangrong Ni, Jun Node Deployment with k-Connectivity in Sensor Networks for Crop Information Full Coverage Monitoring |
title | Node Deployment with k-Connectivity in Sensor Networks for Crop Information Full Coverage Monitoring |
title_full | Node Deployment with k-Connectivity in Sensor Networks for Crop Information Full Coverage Monitoring |
title_fullStr | Node Deployment with k-Connectivity in Sensor Networks for Crop Information Full Coverage Monitoring |
title_full_unstemmed | Node Deployment with k-Connectivity in Sensor Networks for Crop Information Full Coverage Monitoring |
title_short | Node Deployment with k-Connectivity in Sensor Networks for Crop Information Full Coverage Monitoring |
title_sort | node deployment with k-connectivity in sensor networks for crop information full coverage monitoring |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5191076/ https://www.ncbi.nlm.nih.gov/pubmed/27941704 http://dx.doi.org/10.3390/s16122096 |
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